Methods, apparatus, systems and articles of manufacture are disclosed methods and apparatus for audio equalization based on variant selection. An example apparatus includes a processor to obtain training data, the training data including a plurality of reference audio signals each associated with a variant of music and organize the training data into a plurality of entries based on the plurality of reference audio signals, a training model executor to execute a neural network model using the training data, and a model trainer to train the neural network model by updating at least one weight corresponding to one of the entries in the training data when the neural network model does not satisfy a training threshold.
G06N 3/04 - Architecture, e.g. interconnection topology
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
Example methods, apparatus and articles of manufacture (i.e., physical storage media) to perform media source detection based on frequency band selection and processing are disclosed. Example meters disclosed herein are to compare a first audio signal from a monitored media device with a second audio signal from a first one of a plurality of media sources in communication with the monitored media device to determine a sequence of match results, the first audio signal associated with media presented by the media device. Disclosed example meters are also to compute a standard deviation of time delays associated with respective ones of the match results. Disclosed example meters are further to determine whether the first one of the media sources is a source of the media presented by the monitored media device based on the standard deviation.
H04N 21/439 - Processing of audio elementary streams
H04N 7/10 - Adaptations for transmission by electrical cable
H04N 21/41 - Structure of clientStructure of client peripherals
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/436 - Interfacing a local distribution network, e.g. communicating with another STB or inside the home
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/462 - Content or additional data management e.g. creating a master electronic program guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabilities
Example apparatus disclosed herein are to send a request to a media provider that is to cause the media provider to initiate transmission of a transport stream that is to provide streaming media to a media presentation device. Disclosed example apparatus are also to extract metering metadata from a data file to be received by the media presentation device after the transmission of the transport stream is initiated by the media provider but before receipt by the media presentation device of the transport stream that is to provide the streaming media to the media presentation device, the data file associated with the transport stream. Disclosed example apparatus are further to report the metering metadata to a server in response to a detected event, and access an identification of secondary media responsive to the report of the metering metadata, the secondary media to be presented by the media presentation device.
Methods, apparatus, systems and articles of manufacture are disclosed for playback using pre-processed profile information and personalization. Example apparatus disclosed herein include a synchronizer to, in response to receiving a media signal to be played on a playback device, access an equalization (EQ) profile corresponding to the media signal; an EQ personalization manager to generate a personalized EQ setting; and an EQ adjustment implementor to modify playback of the media signal on the playback device based on a blended equalization generated based on the EQ profile and the personalized EQ setting.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
H03F 3/181 - Low-frequency amplifiers, e.g. audio preamplifiers
H04N 9/87 - Regeneration of colour television signals
H04N 21/439 - Processing of audio elementary streams
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
H04R 3/04 - Circuits for transducers for correcting frequency response
5.
METHODS AND APPARATUS TO AUTOMATE RECEIVABILITY UPDATES FOR MEDIA CREDITING
Methods, apparatus, systems, and articles of manufacture are disclosed to automate receivability updates for media crediting. At least one non-transitory machine-readable medium comprises instructions that, when executed, cause at least one processor to at least identify a station identifier associated with at least one of a signature or a code, the at least one of the signature or the code collected at a panelist household. The instructions, when executed, cause at least one processor to further determine whether a household receivability table includes the station identifier, to determine, in response to a determination that the household receivability table does not include a station corresponding to the station identifier, whether the station is receivable at the panelist household, and to update the household receivability table, the update in response to a determination that the station corresponding to the station identifier is receivable at the panelist household.
H04N 21/462 - Content or additional data management e.g. creating a master electronic program guide from data received from the Internet and a Head-end or controlling the complexity of a video stream by scaling the resolution or bit-rate based on the client capabilities
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
6.
METHODS AND APPARATUS TO GENERATE REFERENCE SIGNATURES
Methods and apparatus to generate reference signatures are disclosed. An example method includes collecting a first signature for media being presented to a plurality of households; crediting the media when the first signature matches a reference signature in a reference signature database; in response to determining that the first signature does not match a reference signature in the reference signature database and the first signature does not match an unidentified signature in an unknown signature database, storing the first signature in the unknown signature database; in response to determining that a second signature does not match the reference signature in the reference signature database and the second signature matches the unidentified signature in the unknown signature database, and increasing a count associated with the unidentified signature
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/31 - Arrangements for monitoring the use made of the broadcast services
H04H 60/56 - Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups or
7.
METHODS AND SYSTEMS TO MONITOR A MEDIA DEVICE VIA A USB PORT
An audience measurement computing system for monitoring a media presentation device in a monitored environment is described and includes a network interface, at least one processor, and a non-transitory computer-readable medium comprising instructions executable by the processor(s). The computing system is configured to obtain, via a cable connected to an input port of the media presentation device, a voltage signal generated by the media presentation device based on an operational state of the media presentation device; compare voltage indicated by the voltage signal to a threshold; based on the comparing, generate timestamped operational state data comprising a record indicative of when the media presentation device is in an on-state; obtain audience measurement data representing one or more media signals communicated to the media presentation device; and transmit, via the network interface over a network and to a central facility, the timestamped operational state data and the audience measurement data.
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
In one aspect, an example method includes (i) extracting a sequence of audio features from a portion of a sequence of media content; (ii) extracting a sequence of video features from the portion of the sequence of media content; (iii) providing the sequence of audio features and the sequence of video features as an input to a transition detector neural network that is configured to classify whether or not a given input includes a transition between different content segments; (iv) obtaining from the transition detector neural network classification data corresponding to the input; (v) determining that the classification data is indicative of a transition between different content segments; and (vi) based on determining that the classification data is indicative of a transition between different content segments, outputting transition data indicating that the portion of the sequence of media content includes a transition between different content segments.
G06F 18/2413 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
G06N 3/049 - Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 20/40 - ScenesScene-specific elements in video content
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values associated with the elements. The hash values specify bit positions within an array of bits. Hash values output from the hash logic conform to a geometric distribution such that bit positions of the array of bits corresponding to lower orders bits are more likely to be generated than bit positions corresponding to higher-order bits. Bits of the array of bits corresponding to the bit positions are set. The number of bits of the array of bits that are set is counted. Estimation logic estimates the number of unique elements of the collection of elements as a function of the number of bits of the array of bits that are set.
Disclosed examples access first impression data representative of first impressions collected by an impression monitor system, the first impressions corresponding to the media accessed at a plurality of client devices; generate a panelist impressions composition by removing at least one duplicate impression from second impression data, the second impression data representative of second impressions logged by meters installed at the client devices, the duplicate impression corresponding to one or more accesses to the media represented in both the first impression data and the second impression data for a same audience member; determine an error value for the media based on the panelist impressions composition and a database proprietor impression composition, the database proprietor impression composition provided by a database proprietor for the media; and determine an error-corrected impression composition based on the error value and the panelist impressions composition.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Methods, apparatus, and systems are disclosed to segment audio and determine audio segment similarities. An example apparatus includes at least one memory storing instructions and processor circuitry to execute instructions to at least select an anchor index beat of digital audio, identify a first segment of the digital audio based on the anchor index beat to analyze, the first segment having at least two beats and a respective center beat, concatenate time-frequency data of the at least two beats and the respective center beat to form a matrix of the first segment, generate a first deep feature based on the first segment, the first deep feature indicative of a descriptor of the digital audio, and train internal coefficients to classify the first deep feature as similar to a second deep feature based on the descriptor of the first deep feature and a descriptor of a second deep feature.
A system for prospectively identifying media characteristics for inclusion in media content is disclosed. A neural network database including media characteristic information and feature information may associate relationships among the media characteristic information and feature information. Personal characteristic information associated with target media consumers may be used to select a subset of the neural network database. A first set of nodes, representing selected feature information, may be activated. The node interactions may be calculated to detect the activation of a second set of nodes, the second set of nodes representing media characteristic information. Generally, a node is activated when an activation value of the node exceeds a threshold value. Media characteristic information may be identified for inclusion in media content based on the second set of nodes.
Apparatus, systems, articles of manufacture, and methods for volume adjustment are disclosed herein. An example method includes collecting data corresponding to a volume of an audio signal as the audio signal is output through a device, when an average volume of the audio signal does not satisfy a volume threshold for a specified timespan, determining a difference between the average volume and a desired volume, and applying a gain to the audio signal to adjust the volume of the audio signal to the desired volume, the gain determined based on the difference between the average volume and the desired volume.
An example method is for use in connection with a media device and a motion-detecting device mounted to the media device, and includes: obtaining motion data associated with the motion-detecting device; providing the obtained motion data to a trained classifier, wherein the trained classifier is configured to use at least motion data as runtime input data to generate at least device type data as runtime output data; responsive to providing the obtained motion data to the trained classifier, receiving from the trained classifier corresponding device type data generated by the trained classifier; using at least the received device type data to identify a device type of the media device; using at least the identified device type of the media device as a basis to select a set of configuration parameters for the motion-detecting device; and causing the motion-detecting device to be configured according to the selected set of configuration parameters.
Methods, apparatus, systems and articles of manufacture to identify media sources are disclosed. Example apparatus disclosed herein include an exclusivity determiner, a unique asset identifier, and a signature matcher. The exclusivity determiner is to determine whether media is exclusive to a provider. The unique asset identifier is to associate a first signature of the media with the provider if the media is exclusive to the provider. The signature matcher is to identify the provider based on a second signature, the second signature matching the first signature, the second signature extracted from media presented at a media presentation location.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04L 65/61 - Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio
H04L 65/65 - Network streaming protocols, e.g. real-time transport protocol [RTP] or real-time control protocol [RTCP]
H04N 21/231 - Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers or prioritizing data for deletion
H04N 21/422 - Input-only peripherals, e.g. global positioning system [GPS]
H04N 21/658 - Transmission by the client directed to the server
H04N 21/8352 - Generation of protective data, e.g. certificates involving content or source identification data, e.g. UMID [Unique Material Identifier]
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
16.
Method and System for Estimating the Cardinality of Information
A computer-implemented method for efficiently estimating the number of unique elements in a collection of elements comprises generating, via hash logic, hash values for each element of the collection of elements. The method further comprises specifying, in a sketch-frequency table, a set of discrete statistical values associated with the hash values and, for each discrete statistical value of the set of discrete statistical values, information indicative of a frequency at which binary representations of the hash values are associated with the discrete statistical value. The cardinality of the collection of elements is estimated based on the sketch-frequency table.
Methods, apparatus, systems and articles of manufacture are disclosed to identify media based on historical data. An example method includes: comparing (a) a pitch shifted fingerprint, (b) a time shifted fingerprint, or (c) a resampled fingerprint to a reference fingerprint; in response to a match between any of (a) the pitch shifted fingerprint, (b) the time shifted fingerprint, or (c) the resampled fingerprint and the reference fingerprint, generating indications of (a) a pitch shift value, (b) a time shift value, or (c) a resample ratio that caused the match; in response to collecting broadcast media for a threshold period of time, processing the one or more indications; and in response to a request for a recommendation for information associated with a query, transmitting the recommendation including one or more frequencies of occurrence of (a) the pitch shift value, (b) the time shift value, or (c) the resample ratio.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A media presentation device determines a voice command associated with media content presented by the media presentation device. The media presentation device then listens for and detects utterance of the determined voice command during presentation of the media content, and the media presentation device responds to the detected utterance by performing an action that facilitates user purchase of the good or service associated with the media content segment.
Methods, apparatus, systems, and articles of manufacture are disclosed to determine unique audience size via clustered data. An example apparatus includes memory, machine readable instructions, and processor circuitry to at least one of execute or instantiate the machine readable instructions. The example processor circuitry is to form a first matrix identifying matching and non-matching instances of first values of respective demographics of an audience of media and second values of the respective demographics. Also, the processor circuitry is to normalize the first matrix to generate an account sharing adjustment matrix. Additionally, the processor circuitry is to apply the account sharing adjustment matrix to a vector of one or more counts of impressions of the media to correct for one or more members of the audience that share a user account registered with a database proprietor, the one or more counts of the impressions corresponding to the respective demographics.
G06Q 30/0201 - Market modellingMarket analysisCollecting market data
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
20.
Use of Audio Classification as Basis to Control Audio Identification
A method includes receiving, into a microphone of a portable computing device, audio from a surrounding environment of the portable computing device. The method also includes classifying, by the portable computing device, the received audio as containing media content or as containing no media content. Classifying the received audio as containing media content or as containing no media content comprises determining whether the audio defines content emitted from a media player in the surrounding environment of the portable computing device. The method further includes, based on the classifying, controlling by the portable computing device whether to engage in an audio-identification process for determining an identity of the media content.
Methods and apparatus are disclosed to determine a power state of a device. An example method includes determining respective counts for a plurality of measurements during a calibration period, the measurements indicative of an amount of power drawn by the device, determining a first threshold and a second threshold based on at least one of the counts, the first threshold determined using most frequently logged measurement values, the most frequently logged measurement values based on counts performed after expiration of the calibration period, comparing a measurement to the first threshold and to the second threshold, and outputting a positive indication when the measurement is within an acceptable difference range, the acceptable difference range based on the amount of power drawn by the device.
H04N 17/00 - Diagnosis, testing or measuring for television systems or their details
G01R 35/00 - Testing or calibrating of apparatus covered by the other groups of this subclass
H04H 60/32 - Arrangements for monitoring conditions of receiving stations, e.g. malfunction or breakdown of receiving stations
H04N 5/64 - Constructional details of receivers, e.g. cabinets or dust covers
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
22.
METHODS AND APPARATUS TO DETECT AND RECTIFY FALSE SET TOP BOX TUNING DATA
Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/658 - Transmission by the client directed to the server
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
23.
METHODS AND APPARATUS TO DETERMINE MEDIA EXPOSURE OF A PANELIST
Methods, apparatus, systems and articles of manufacture to determine media exposure of a panelist are disclosed. An example apparatus include memory; computer readable instructions; and processor circuitry to execute the computer readable instructions to: determine an anonymized identifier from media monitoring data corresponding to a personal people meter of a panelist; filter anonymized census data from a plurality of media devices based on the anonymized identifier; when second media data different than first media data is included in the media monitoring data during a same time duration, tag the time duration as corresponding to multiple media exposure; and credit exposure to media for the panelist based on the tag.
A system and method for attributing media-exposure to a particular media-delivery device, such as a media player, at a panelist site. An example system includes a first meter configured to detect media presentation by a media-presentation device at the panelist site, and a second meter configured to detect media transmission at the panelist site to the media-delivery device at the panelist site. Further, the example system includes program instructions stored in non-transitory data storage and executable by at least one processor to carry out operations including (i) correlating the detected media presentation at the panelist site with the detected media transmission at the panelist site to the media-delivery device at the panelist site and (ii) based on the correlating, associating the panelist media-exposure with the media-delivery device, such as by generating record indicating the association. This association may then be used as a basis to enhance audience ratings.
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
H04N 21/658 - Transmission by the client directed to the server
Example systems and methods are audio identification based on data structure are disclosed. An example apparatus includes memory, and one or more processors to execute instructions to execute a constant Q transform on query time slices of query audio, binarize the constant Q transformed query time slices, execute a two-dimensional Fourier transform on query time windows within the binarized and constant Q transformed query time slices to generate two-dimensional Fourier transforms of the query time windows, sequentially order the two-dimensional Fourier transforms in a query data structure, and identify the query audio as a cover rendition of reference audio based on a comparison between the query data structure and a reference data structure associated with the reference audio.
G06F 17/14 - Fourier, Walsh or analogous domain transformations
G10L 25/27 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
26.
METHODS AND APPARATUS TO GENERATE AUDIENCE METRICS FOR CONNECTED TELEVISION
Methods, apparatus, systems, and articles of manufacture are disclosed to generate audience metrics for connected television. An example system includes at least one memory, programmable circuitry, and instructions to cause the programmable circuitry to obtain media access data corresponding to connected television media and a user identifier corresponding to a media access device, generate, using a machine learning model, probability values for corresponding audience demographics in a household composition corresponding to the user identifier, the probability values indicative of likelihoods that corresponding ones of the audience demographics are accessing the connected television media, determine a person-level characteristic based on the probability values of the audience demographics, the person-level characteristic corresponding to an audience member of the connected television media, and assign the media access data to the person-level characteristic.
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
27.
APPARATUS, SYSTEMS, AND METHODS FOR USER PRESENCE DETECTION FOR AUDIENCE MONITORING
Apparatus, systems, and method for user presence detection for audience monitoring are disclosed. Example apparatus disclosed herein are to detect movement of a user relative to an area based on one or more signals output by one or more motion detection sensors, the area associated with a media presentation device. Disclosed example apparatus are also to generate a request for verification of user presence in the viewing area in response to detection of the user movement. Disclosed example apparatus are further to correlate a user input responsive to the request with media presented via the media presentation device.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
Example methods and apparatus to improve timestamp transition resolution of watermarks are disclosed. A disclosed example apparatus is to determine an initial resolution for timestamp transitions based on a first number of time units between first ones of watermarks detected in media, and determine an updated resolution for the timestamp transitions based on a predicted timestamp transition window and a second number of time units between second ones of the watermarks detected in the media, the second ones of the watermarks to be subsequent to the first ones of the watermarks in the media, the predicted timestamp transition window associated with the initial resolution for timestamp transitions, the updated resolution for the timestamp transitions corresponding to a third number of time units, the third number of time units less than the second number of time units.
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
G10L 25/45 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of analysis window
H04N 19/467 - Embedding additional information in the video signal during the compression process characterised by the embedded information being invisible, e.g. watermarking
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video streamElementary client operations, e.g. monitoring of home network or synchronizing decoder's clockClient middleware
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 21/8547 - Content authoring involving timestamps for synchronizing content
29.
Methods and Apparatus for Efficient Media Indexing
Methods, apparatus, systems and articles of manufacture are disclosed for efficient media indexing. An example method disclosed herein includes means for initiating a list of hash seeds, the list of hash seeds including at least a first hash seed value and a second hash seed value among other hash seed values, means for generating to generate a first bucket distribution based on the first hash seed value and a first hash function and generate a second bucket distribution based on the second hash seed value used in combination with the first hash seed value, means for determining to determine a first entropy value of the first bucket distribution, wherein data associated with the first bucket distribution is stored in a first hash table and determine a second entropy value of the second bucket distribution.
A method system for use of Doppler shift as a basis to detect user focus, such as to detect that a user was attracted to audio media and/or to an associated object. A portable processing device carried by the user receives audio media emitted from an audio source at a fixed location, the audio media having periodic watermarking encoded at a baseline frequency. The portable processing device detects a change in frequency of the periodic watermarking over time, such as the frequency progressing from at least being higher than the baseline frequency to being the baseline frequency for at least a predefined threshold period of time. Based on the detected change in frequency of the periodic watermarking over time, the portable device then provides a report indicating that the user was attracted to the audio media and/or to an object (e.g., a commercial object) collocated with the audio source.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G01S 15/58 - Velocity or trajectory determination systemsSense-of-movement determination systems
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
H04N 21/439 - Processing of audio elementary streams
31.
METHODS AND APPARATUS FOR AFFILIATE INTERRUPT DETECTION
Methods, apparatus, systems and articles of manufacture are disclosed for affiliate interrupt detection. An example method disclosed herein includes determining whether a first time period of a first audio signal corresponds to a first affiliate interrupt period based on whether (1) a first type of watermark is detected in the first time period of the first audio signal, and (2) a second type of watermark is detected in the first audio signal outside the first time period but not in the first time period of the first audio signal, and determining whether the first time period of the first audio signal corresponds to the first affiliate interrupt period when watermarks are not detected in the first time period of the first audio signal based on comparison of first signatures with second signatures representing a corresponding first time period of a reference audio signal.
H04N 21/2389 - Multiplex stream processing, e.g. multiplex stream encrypting
H04N 21/233 - Processing of audio elementary streams
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
H04N 21/262 - Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission or generating play-lists
Example apparatus disclosed herein are to obtain a first hash key, a second hash key and a third hash key representative of first reference media in response to a first query of a first table, the second hash key associated with a second time preceding a first time associated with the first hash key, the third hash key associated with a third time following the first time associated with the first hash key. Disclosed example apparatus are also to prequalify the first hash key as a candidate for subsequent signature processing associated with a first site signature in response to a determination that the second hash key corresponds to a second site signature preceding the first site signature in time and that the third hash key corresponds to a third site signature following the first site signature in time.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G06V 20/40 - ScenesScene-specific elements in video content
H04H 60/31 - Arrangements for monitoring the use made of the broadcast services
H04H 60/40 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying broadcast time or space for identifying broadcast time
H04H 60/56 - Arrangements characterised by components specially adapted for monitoring, identification or recognition covered by groups or
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/4408 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs involving video stream encryption, e.g. re-encrypting a decrypted video stream for redistribution in a home network
H04N 21/8352 - Generation of protective data, e.g. certificates involving content or source identification data, e.g. UMID [Unique Material Identifier]
Methods, apparatus, systems, and articles of manufacture are disclosed to identify main page views. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to: access a log of requests from a proxy, the log of requests including main page requests and embedded page requests, the log of requests including timestamps corresponding to the main page requests and the embedded page requests, identify, based on consecutive ones of the timestamps occurring within a time interval, at least one of the main page requests associated with the time interval, and credit the at least one of the main page requests as a main page view.
Disclosed examples include logging impression records corresponding to pingback messages received in network communications from a client device, ones of the pingback messages corresponding to portions of media presented at the client device; determining a duration impression for the media based on the impression records; dividing the duration impression based on media types corresponding to the portions of the media presented at the client device; and determining demographic characteristics for ones of the media types in the portions of the media.
Methods, apparatus, systems, and articles of manufacture to accurately credit streaming sessions are disclosed. A meter device records streaming session information. Cluster creation circuitry trains a model by grouping information from multiple streaming sessions into clusters, wherein all streaming sessions within a given cluster have matching media and streaming sources. Model executor circuitry assigns incoming streaming session information to a cluster or to noise. Cluster creation circuitry edits the model by creating new clusters out of information from multiple streaming sessions with similar attributes that were originally labeled as noise. By only crediting streaming session information assigned to a cluster, the disclosed system avoids crediting illogical streaming session information, such as the crediting of media to a streaming source that does not offer said media.
Methods, apparatus, systems, and articles of manufacture are disclosed to generate synthetic respondent level data. Example apparatus disclosed herein include means for generating a synthetic panel corresponding to a duration of time, the means for generating the synthetic panel to: generate a transition matrix corresponding to a first sub-duration of the duration of time and a second sub-duration of the duration of time; generate, based on the transition matrix, a plurality of synthetic panelists and associated viewing data; remove first ones of the synthetic panelists associated with one or more weights that do not satisfy a threshold to generate the synthetic panel corresponding to the duration of time, the synthetic panel representative of audiences of media presented by a plurality of media devices during the duration of time; and generate synthetic respondent level data based on the viewing data associated with remaining second ones of the synthetic panelists.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/31 - Arrangements for monitoring the use made of the broadcast services
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/262 - Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission or generating play-lists
H04N 21/458 - Scheduling content for creating a personalised stream, e.g. by combining a locally stored advertisement with an incoming streamUpdating operations, e.g. for OS modules
Methods, apparatus, systems, and articles of manufacture are disclosed to identify media for ahead of time watermark encoding. An example apparatus includes a media interface to determine a characteristic of media, the characteristic corresponding to a broadcast time of the media; and a controller to: determine an identifier corresponding to the media; transmit a query including the characteristic and the identifier prior to the media being broadcast, the query to request an indication whether the identifier is unique; and responsive to the indication that the identifier is unique, cause a watermark to be encoded in the media using the identifier prior to the media being broadcast.
H04N 21/262 - Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission or generating play-lists
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
38.
METHODS AND APPARATUS FOR MULTIMODAL AUDIENCE DETECTION AND IDENTIFICATION
Methods, apparatus, systems and articles of manufacture are disclosed for multimodal audience detection and identification. An example system disclosed herein includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: select a portion of a set of signal strength values associated with advertising packets from a device associated with a user, the advertising packets captured by a multi-axis receiver on a plurality of different signal polarizations; calculate a first representative signal strength value based on the selected portion of signal strength values; and determine a presence of the user based on whether the first representative signal strength value satisfies a threshold.
G01S 13/04 - Systems determining presence of a target
G01S 7/41 - Details of systems according to groups , , of systems according to group using analysis of echo signal for target characterisationTarget signatureTarget cross-section
G01S 11/06 - Systems for determining distance or velocity not using reflection or reradiation using radio waves using intensity measurements
H04N 21/41 - Structure of clientStructure of client peripherals
H04W 4/80 - Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
H04W 64/00 - Locating users or terminals for network management purposes, e.g. mobility management
Techniques of providing motion video content along with audio content are disclosed. In some example embodiments, a computer-implemented system is configured to perform operations comprising: receiving primary audio content; determining that at least one reference audio content satisfies a predetermined similarity threshold based on a comparison of the primary audio content with the at least one reference audio content; for each one of the at least one reference audio content, identifying motion video content based on the motion video content being stored in association with the one of the at least one reference audio content and not stored in association with the primary audio content; and causing the identified motion video content to be displayed on a device concurrently with a presentation of the primary audio content on the device.
H04N 21/43 - Processing of content or additional data, e.g. demultiplexing additional data from a digital video streamElementary client operations, e.g. monitoring of home network or synchronizing decoder's clockClient middleware
H04N 21/439 - Processing of audio elementary streams
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
40.
METHODS AND APPARATUS TO IDENTIFY MEDIA APPLICATION SESSIONS
Methods and apparatus to identify media application sessions are disclosed. An example apparatus includes an audio interface to monitor an audio output of a media presentation device during a viewing session, a tone analyzer to identify one or more dual-tone multi-frequency (DTMF) tones presented by the audio output of the media presentation device, a session identification determiner to determine a session identification value associated with the viewing session based on the one or more identified DTMF tones, and a session report generator to associate a panelist identifier with the viewing session, and generate a session report based on the session identification value associated with the DTMF tones and the panelist identifier associated with the viewing session.
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
Methods and apparatus are disclosed for supplementing partially readable and/or inaccurate codes. An example apparatus includes a watermark analyzer to select a first watermark and a second watermark decoded from media; a comparator to compare a first decoded timestamp of the first watermark to a second decoded timestamp of the second watermark; and a timestamp adjuster to adjust the second decoded timestamp based on the first decoded timestamp of the second watermark when at least a threshold number of symbols of the second decoded timestamp match corresponding symbols of the first decoded timestamp.
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
G10L 19/02 - Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocodersCoding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
42.
METHODS AND APPARATUS FOR LOADING AND ROLL-OFF OF REFERENCE MEDIA ASSETS
Methods, apparatus, systems, and articles of manufacture are disclosed for loading and roll-off of reference media assets. Example apparatus disclosed herein are to determine whether a first condition to prune a reference media asset is satisfied, and in response to a determination that the first condition is satisfied, determine whether a second condition to prune the reference media asset is satisfied. Disclosed example apparatus are also to, in response to a determination that the second condition is satisfied: segment the reference media asset into a plurality of segments based on a length of the reference media asset, prune a first one of the segments, and retain a second one of the segments in a database to compare with meter data to credit media exposure associated with the reference media asset.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
43.
METHODS AND APPARATUS TO CORRELATE A DEMOGRAPHIC SEGMENT WITH A FIXED DEVICE
Methods, apparatus, systems, and articles of manufacture to correlate a demographic segment with a fixed device are disclosed. An example method includes accessing a record indicating a public Internet Protocol (IP) address used by a fixed device. A monitoring data record received from a mobile device is accessed. A demographic segment of a user of the mobile device is determined. The mobile device is associated with the fixed device when an IP address of the mobile device from the monitoring data record matches the public IP address used by the fixed device. The demographic segment of the user of the mobile device is associated with the fixed device based on the association of the fixed device and the mobile device.
Methods, apparatus, and systems are disclosed for estimating audience exposure based on engagement level. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify a user activity associated with a user during exposure of the user to media based on an output from at least one of a user device, a remote control device, an image sensor, or a motion sensor, classify the user activity as an attention-based activity or a distraction-based activity, assign a distraction factor or an attention factor to the user activity based on the classification, and determine an attention level for the user based on the distraction factor or the attention factor.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
45.
METHODS AND APPARATUS TO IDENTIFY MEDIA BASED ON WATERMARKS ACROSS DIFFERENT AUDIO STREAMS AND/OR DIFFERENT WATERMARKING TECHNIQUES
Example apparatus disclosed herein are to detect a first watermark embedded in an audio stream associated with media, the first watermark embedded and detected based on a first watermarking technique; and detect a second watermark embedded in the audio stream, the second watermark embedded and detected based on a second watermarking technique. Disclosed example apparatus are also to assign the first watermark to a first monitoring track and to a second monitoring track, the first monitoring track limited to watermarks embedded in the audio stream based on the first watermarking technique, the second monitoring track limited to watermarks embedded in the audio stream based on any of the first or second watermarking techniques; group the first and second watermarks to form a media detection event when the second watermark is assigned to the second monitoring track; and cause transmission of the media detection event to a data collection facility.
H04N 21/439 - Processing of audio elementary streams
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/83 - Generation or processing of protective or descriptive data associated with contentContent structuring
46.
Use of Steganographically-Encoded Data as Basis to Disambiguate Fingerprint-Based Channel-Multi-Match
The disclosure provides for use of steganographically-encoded data as a basis to disambiguated a fingerprint-based channel-multimatch. A fingerprint-matching server or other entity could detect a channel-multi-match scenario by determining that query fingerprints representing media content being rendered by a content presentation device match reference fingerprints respectively representing multiple channels. In view of that detected channel-multi-match scenario, the content presentation device could then provide channel-identification information that the content presentation device extracts from a watermark that is steganographically encoded in the media content of the channel that the content presentation device is rendering, for use of the extracted channel-identification information to determine which channel the content presentation device is rendering. Identifying the channel being rendered could then facilitate channel-specific action, such as then detecting a content-modification opportunity on the identified channel and preparing and enabling the content presentation device to carry out an associated content modification.
H04N 21/2389 - Multiplex stream processing, e.g. multiplex stream encrypting
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
Methods, apparatus, systems, and articles of manufacture are disclosed to determine a duration of media presentation based on tuning session duration. Example apparatus a receiver to obtain a first tuning session duration indicative of an amount of time between channel changes of a first media presentation device at a first media presentation location, a presentation session estimator to select a model from storage, the model selected based on a match of the first tuning session duration and a second tuning session duration, the model including a relation between the second tuning session duration and a first presentation session duration of media presented on a second media presentation device at a second media presentation location, and estimate a second presentation session duration of media presented within the first tuning session duration based on the model.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
48.
Communication of Payload Data Through Altered Sequence of Metadata Defining Audio-Rendering Directives
To facilitate communicating payload data to a destination, a computing system varies audio-rendering-directive metadata over time in a manner that represents the payload data and outputs the varied audio-rendering-directive metadata over time for communication along with an audio stream to the destination to facilitate rendering of the audio stream at the destination in accordance with the varied audio-rendering-directive metadata over time. The rendering of the audio stream at the destination conveys the payload data by being in accordance with the varied audio-rendering-directive metadata over time that represents the payload data. Thus, an audio meter operating at the destination could detect associated variation in the rendered audio stream and map that detected variation in the rendered audio stream to the payload data, thereby receiving the payload data. Varying the audio-rendering-directive metadata over time could involve varying audio-loudness specifications over time and/or varying spatial-audio specifications over time, among other possibilities.
To facilitate communicating payload data to a destination, a computing system varies audio-rendering-directive metadata over time in a manner that represents the payload data and outputs the varied audio-rendering-directive metadata over time for communication along with an audio stream to the destination to facilitate rendering of the audio stream at the destination in accordance with the varied audio-rendering-directive metadata over time. The rendering of the audio stream at the destination conveys the payload data by being in accordance with the varied audio-rendering-directive metadata over time that represents the payload data. Thus, an audio meter operating at the destination could detect associated variation in the rendered audio stream and map that detected variation in the rendered audio stream to the payload data, thereby receiving the payload data. Varying the audio-rendering-directive metadata over time could involve varying audio-loudness specifications over time and/or varying spatial-audio specifications over time, among other possibilities.
To extract an identifier value from a watermark in media content, a system initially determines the identifier by determining symbol values based on an evaluation of tone strength of each of multiple symbol time segments of the watermark. Further, the system assigns a quality level to the watermark, based on a count of errors in the determined symbol values in view of one or more watermark-structure rules. Still further, if the quality level is threshold low, then the system engages in an error correction process that takes into account, for each symbol time segment whose symbol value may be erroneous, whether that symbol time segment has a threshold strong tone combination that matches the tone combination of a corresponding symbol time segment in a verified watermark. And if the error correction process is successful, the system replaces the determined identifier value with the identifier value of the verified watermark.
Methods, apparatus, systems and articles of manufacture to perform media device asset qualification are disclosed. An example apparatus includes at least one memory, and at least one processor to execute instructions to at least identify a first set of candidate media device assets for disqualification, the candidate media device assets including A) a signature and B) a media identifier that identifies media, generate a hash table using a second set of the candidate media device assets, determine one or more counts of matches between C) a first signature and a first media identifier of a first candidate media device asset of the second set and D) respective signatures and media identifiers of multiple ones of the second set using the hash table, the multiple ones of the second set not including the first candidate media device asset, and load the first signature into a reference database as a reference signature.
H04N 21/254 - Management at additional data server, e.g. shopping server or rights management server
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/41 - Structure of clientStructure of client peripherals
H04N 21/439 - Processing of audio elementary streams
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/6543 - Transmission by server directed to the client for forcing some client operations, e.g. recording
Systems, methods, and apparatus to identify media devices are disclosed. An example network communications monitor includes network interface circuitry, computer readable instructions, and processor circuitry. The processor circuitry is to execute the computer readable instructions to detect, via the network interface circuitry, multiple network communications transmitted on a home network within the household, access panelist data that associates a panelist of the household with a panelist device of the panelist, determine, based on the panelist data, that one or more of the multiple network communications are associated with the panelist device, and cause storage of data identifying the one or more network communications in association with the panelist.
H04H 60/32 - Arrangements for monitoring conditions of receiving stations, e.g. malfunction or breakdown of receiving stations
H04L 61/103 - Mapping addresses of different types across network layers, e.g. resolution of network layer into physical layer addresses or address resolution protocol [ARP]
H04L 61/2514 - Translation of Internet protocol [IP] addresses between local and global IP addresses
H04L 61/5014 - Internet protocol [IP] addresses using dynamic host configuration protocol [DHCP] or bootstrap protocol [BOOTP]
53.
METHODS AND APPARATUS FOR WIRELESS COMMUNICATION WITH AN AUDIENCE MEASUREMENT DEVICE
Methods, apparatus, systems, and articles of manufacture for communication with an audience metering device are disclosed. An example apparatus includes one or more non-transitory computer readable media, instructions in the apparatus, and one or more processors to execute the instructions. The example one or more processors are to segment a message to be transmitted to a configuration device into a first message segment and a second message segment, store the first message segment in a characteristic memory, and transmit a first advertisement to the configuration device when the first message segment is stored in the characteristic memory. Additionally, the example one or more processors are to after the first message segment has been gathered by the configuration device, store the second message segment in the characteristic memory and transmit a second advertisement to the configuration device when the second message segment is stored in the characteristic memory.
Methods and apparatus to estimate audience sizes using deduplication based on vector of counts sketch data are disclosed. A system includes hardware circuitry to instantiate: coefficient analyzer circuitry to determine coefficient values of a polynomial based on (i) variances in values in a first vector of counts and a second vector of counts, (ii) a first cardinality of the first vector of counts, and (iii) a second cardinality of the second vector of counts; and overlap analyzer circuitry to: determine a real root of the polynomial; and report generator circuitry to estimate a deduplicated audience size based on (i) the estimate of the quantity of the second subscribers that are duplicates of the first subscribers and (ii) the first and second cardinalities. The system includes communication circuitry to transmit a network communication to a third party entity, the second network communication including a report based on the deduplicated audience size.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
55.
METHODS AND APPARATUS OF MEDIA DEVICE DETECTION FOR MINIMALLY INVASIVE MEDIA METERS
Methods, apparatus, systems and articles of manufacture are disclosed for media crediting and, more particularly, methods and apparatus of media device detection for media meters. An example computing system disclosed herein to detect media devices presenting media comprises a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by the processor, cause performance of a set of operations comprising generating a cluster of media locations based on media identifying information received from a presentation of media at a streaming media device and identifying the streaming media device based on the media devices available at the media locations in the cluster of media locations and an identity of a media device determined to be available in a majority of media locations in the cluster of media locations.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/00 - Arrangements for broadcast applications with a direct linkage to broadcast information or to broadcast space-timeBroadcast-related systems
H04H 60/29 - Arrangements for monitoring broadcast services or broadcast-related services
H04H 60/54 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying locations where broadcast information is generated
H04N 21/2547 - Third party billing, e.g. billing of advertiser
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/435 - Processing of additional data, e.g. decrypting of additional data or reconstructing software from modules extracted from the transport stream
H04N 21/658 - Transmission by the client directed to the server
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
56.
Use of Steganographically-Encoded Time Information as Basis to Establish a Time Offset, to Facilitate Taking Content-Related Action
A method and system for using steganographically-encoded time information as a basis to control when a client carries out a content-related action. The client processes for presentation one or more linear media streams, each defining a respective time sequence of frames of media content, and at least one of the streams being steganographically encoded with at least one watermark at a respective time-point within the linear media stream, the watermark encoding a timestamp of the respective time-point within the linear media stream according to a server clock. The client extracts the timestamp from the watermark and computes a time offset based on a difference between the extracted timestamp and a current time according to a client clock. And the client uses the computed time offset as a basis to determine when to carry out a content-related action in a given one of the one or more linear media streams.
H04N 21/2389 - Multiplex stream processing, e.g. multiplex stream encrypting
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
Methods, apparatus, systems and articles of manufacture are disclosed to associate geographic locations with user devices. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to extract source identifying information from a beacon transmitted from a user device to an audience measurement entity, classify a network that connects the user device to the audience measurement entity based on the source identifying information, query a location service of a provider of a mobile network to retrieve a location associated with the user device, store the location in association with media identifying information, and generate a user profile associating the user device with the retrieved location.
Methods and apparatus to monitor media presentations are disclosed. Example methods disclosed herein include presenting information via a display of a media device, the information indicating that monitor software in the media device can be enabled, the monitor software to monitor media presented by the media device, the monitor software to be disabled by default. Disclosed example methods also include detecting a first user input that is to authorize the monitor software in the media device to be enabled, and in response to detection of the first user input: (i) enabling the monitor software in the media device to generate and report at least one of video fingerprints, audio fingerprints, video watermarks or audio watermarks representative of media presented by the media device, and (ii) transmitting, via a network interface, a notification to a remote monitoring entity to indicate that the monitor software in the media device has been enabled.
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/658 - Transmission by the client directed to the server
Methods and apparatus are disclosed to monitory online activity. An example apparatus includes at least one memory, instructions, and processor circuitry to execute the instructions to generate a first database to store first uniform resource locators collected from first client devices, the first client devices associated with panelists, generate a second database to store second uniform resource locators collected from second client devices, one or more of the second client devices associated with one or more unidentified users, associate at least one of the second uniform resource locators as online activity of a first panelist of the panelists based on at least a portion of one of the first uniform resource locators matching at least a portion of the one of the second uniform resource locators, and store an association of the online activity and an identifier, the identifier to identify the first panelist.
Example methods, apparatus, systems and articles of manufacture to determine synthetic total audience ratings are disclosed. Disclosed example apparatus are to access census data including census viewing statements associated with media content presented by census devices, access panel data including panelist viewing statements associated with media content presented by panel devices, the panel data including weights to represent numbers of individuals to be represented by corresponding panelists, determine scores representing similarities between ones of a first group of census devices determined to having matching panel devices in the panel data and ones of a second group of census devices determined to be unmatched in the panel data, and assign the census devices to the panel devices based on the scores and the weights.
H04N 21/25 - Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication or learning user preferences for recommending movies
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
Example systems and methods for automated cover song identification are disclosed. An example apparatus includes at least one memory, machine-readable instructions, and one or more processors to execute the machine-readable instructions to at least execute a constant Q transform on time slices of first audio data to output constant Q transformed time slices, binarize the constant Q transformed time slices to output binarized and constant Q transformed time slices, execute a two-dimensional Fourier transform on time windows within the binarized and constant Q transformed time slices to output two-dimensional Fourier transforms of the time windows, generate a reference data structure based on a sequential order of the two-dimensional Fourier transforms, store the reference data structure in a database, and identify a query data structure associated with query audio data as a cover rendition of the audio data based on a comparison of the query and reference data structures.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Methods, apparatus, systems, and articles of manufacture are disclosed to estimate population reach from marginal ratings. An example apparatus includes means for iteratively converging on an output estimate of a reach of media for a total population audience and means for outputting the estimate of the reach for the total population audience.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G06Q 30/0201 - Market modellingMarket analysisCollecting market data
H04N 21/475 - End-user interface for inputting end-user data, e.g. PIN [Personal Identification Number] or preference data
A method implemented by a computing system comprises generating, by the computing system, a fingerprint comprising a plurality of bin samples associated with audio content. Each bin sample is specified within a frame of the fingerprint and is associated with one of a plurality of non-overlapping frequency ranges and a value indicative of a magnitude of energy associated with a corresponding frequency range. The computing system removes, from the fingerprint, a plurality of bin samples associated with a frequency sweep in the audio content.
G10L 25/54 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for retrieval
G10L 19/018 - Audio watermarking, i.e. embedding inaudible data in the audio signal
G10L 19/028 - Noise substitution, e.g. substituting non-tonal spectral components by noisy source
G10L 25/18 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
G10L 25/27 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique
G10L 25/72 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for transmitting results of analysis
Audience monitoring systems and related methods are described herein. An example audience monitoring system includes a beacon to be disposed proximate a media presentation device. The beacon is to transmit a ping signal. The system also includes a portable metering device to be carried by a person. The portable metering device includes a microphone to receive an audio signal and a processor to determine a distance value indicative of a distance between the portable metering device and the beacon based on the ping signal.
H04Q 9/00 - Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom
Methods, apparatus, systems, and articles of manufacture are disclosed for measuring engagement during media exposure. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to at least one of instantiate or execute the machine readable instructions to identify media presented via a media device in a media presentation environment, identify ambient audio detected in the media presentation environment, determine whether the ambient audio is distractive to presentation of the media in the media presentation environment, and adjust a media exposure report based on a determination that the ambient audio is distractive.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
66.
Methods and Apparatus to Fingerprint an Audio Signal Via Exponential Normalization
Methods, apparatus, systems, and articles of manufacture are disclosed to fingerprint an audio signal via exponential normalization. An example apparatus includes an audio segmenter to divide an audio signal into a plurality of audio segments including a first audio segment and a second audio segment, the first audio segment including a first time-frequency bin, the second audio segment including a second time-frequency bin, a mean calculator to determine a first exponential mean value associated with the first time frequency bin based on a first magnitude of the audio signal associated with the first time frequency bin and a second exponential mean value associated with the second time frequency bin based on a second magnitude of the audio signal associated with the second time frequency bin and the first exponential mean value. The example apparatus further includes a bin normalizer to normalize the first time-frequency bin based on the second exponential mean value and a fingerprint generator to generate a fingerprint of the audio signal based on the normalized first time-frequency bins.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G10L 25/21 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being power information
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
67.
POWER EFFICIENT DETECTION OF WATERMARKS IN MEDIA SIGNALS
Example apparatus disclosed herein include a watermark detector to detect watermarks in a media signal. Disclosed example apparatus also include a controller to operate the watermark detector to (1) detect a first watermark in the media signal, and (2) cycle between sleep intervals and active intervals based on a repetition rate of the watermarks in the media signal to perform a detection operation for a second watermark at a second location in the media signal relative to a first location of the first watermark in the media signal. In some examples, the controller is to search a buffer of prior detected watermark symbols to detect a third watermark at a third location prior to the second location in the media signal in response to the second watermark not being detected at the second location in the media signal.
H04N 19/42 - Methods or arrangements for coding, decoding, compressing or decompressing digital video signals characterised by implementation details or hardware specially adapted for video compression or decompression, e.g. dedicated software implementation
H04N 19/467 - Embedding additional information in the video signal during the compression process characterised by the embedded information being invisible, e.g. watermarking
H04N 21/439 - Processing of audio elementary streams
H04N 21/443 - OS processes, e.g. booting an STB, implementing a Java virtual machine in an STB or power management in an STB
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
68.
METHODS AND APPARATUS TO CREDIT MEDIA SEGMENTS SHARED AMONG MULTIPLE MEDIA ASSETS
Methods, apparatus, systems and articles of manufacture to credit media segments shared among multiple media assets are disclosed. Example methods disclosed herein include comparing a sequence of monitored media signatures with a library of reference signatures to determine a signature match, the monitored media signatures representative of a monitored media presentation. Disclosed example methods also include determining duration and offset of the signature match, the offset to represent a position of the signature match relative to a start of a reference media asset associated with the signature match. Disclosed example methods further include crediting a segment of the monitored media presentation represented by the signature match to an identifier of a class of media assets including the reference media asset in response to a determination that (i) the duration of the signature match does not exceed a first threshold and (ii) the offset does not exceed a second threshold.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/235 - Processing of additional data, e.g. scrambling of additional data or processing content descriptors
H04N 21/44 - Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream or rendering scenes according to encoded video stream scene graphs
69.
Display device on/off detection methods and apparatus
Display device ON/OFF detection methods and apparatus are disclosed. Example display activity detectors disclosed herein are to extract regions from respective ones of captured video frames, the regions corresponding to a depiction of a display of a monitored media device Disclosed example display activity detectors are also to compute a distance metric that is to represent an amount a first one of the regions of a first one of the captured video frames differs from a corresponding second one of the regions of a second one of the captured video frames. Disclosed example display activity detectors are further to compare the distance metric to a threshold to determine whether the monitored media device is ON or OFF.
An example system disclosed herein includes programmable circuitry to identify donor adjustment factors and recipient adjustment factors used for correction of media impressions logged by a database proprietor, the donor adjustment factors including first donor adjustment factors associated with a first geographic region and second donor adjustment factors associated with a second geographic region, determine a first reduced donor factor set corresponding to ones of the first donor adjustment factors that satisfy a threshold, determine a second reduced donor factor set corresponding to ones of the second donor adjustment factors that satisfy the threshold, and generate imputation factors based on an aggregation of retained ones of the donor adjustment factors, the retained ones of the donor adjustment factors selected based on the first reduced donor factor set and the second reduced donor factor set, the imputation factors to reduce error in the correction.
Examples to determine media impressions using distributed demographic information are disclosed. An example system includes programmable circuitry to log, at a first Internet domain, a first record for a first website visit by a first client device to a website at a second Internet domain, the first record based on a hypertext transfer protocol (HTTP) request, the first record to include a timestamp, a uniform resource locator (URL), and a user identifier, the timestamp to represent a time of the first website visit, the URL corresponding to the website at the second Internet domain, and weight impression data in a report, the impression data associated with the first record and with second records, the second records corresponding to second website visits to the website via second client devices, the weighting of the impression data based on demographic distributions of audience members corresponding to the first and second records.
Methods, apparatus, systems, and articles of manufacture are disclosed to determine whether audience measurement meters are co-located. An example apparatus is to, based on a difference between a first sampling time of a first entry of a first log and a second sampling time of a corresponding entry of a second log satisfying a first threshold, determine at least one matching instance of at least one first device identifier of the first entry and at least one second device identifier of the corresponding entry. Additionally, the example apparatus is to populate a variable with the at least one matching instance. The example apparatus is also to, based on a metric satisfying a second threshold, cause transmission of an alert indicating that a first meter and a second meter were co-located during generation of the first log and the second log, the metric based on the at least one matching instance.
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
73.
METHODS AND APPARATUS TO DETERMINE AUDIENCE ENGAGEMENT
Methods, apparatus, systems, and articles of manufacture are disclosed. An example system includes: interface circuitry; programmable circuitry; and instructions to program the programmable circuitry to: obtain audio of a media presentation; obtain ambient noise in an area associated with the media presentation; determine an intensity of a difference between the audio and the ambient noise; and determine an engagement level of an audience of the media presentation based on a duration the intensity satisfies a threshold value.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
Methods, apparatus, systems and articles of manufacture are disclosed for audio equalization. Example instructions disclosed herein cause one or more processors to at least: detect an irregularity in a frequency representation of an audio signal in response to a change in volume between a set of frequency values exceeding a threshold; and adjust a volume at a first frequency value of the set of frequency values to reduce the irregularity.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
H03F 3/181 - Low-frequency amplifiers, e.g. audio preamplifiers
H04N 9/87 - Regeneration of colour television signals
H04N 21/439 - Processing of audio elementary streams
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
H04R 3/04 - Circuits for transducers for correcting frequency response
75.
METHODS AND APPARATUS TO MONITOR WI-FI MEDIA STREAMING USING AN ALTERNATE ACCESS POINT
Methods, apparatus, systems and articles of manufacture are disclosed to monitor wireless traffic. An example apparatus disclosed herein includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: establish, via a first wireless interface, a wireless connection with first network credentials to match second network credentials of a primary access point; monitor traffic via a second wireless interface, the second wireless interface different than the first wireless interface; identify, via the traffic monitored via the second wireless interface, a connection of a client to the primary access point; capture, via an alternate access point, a management frame transmitted from the primary access point to the client; insert a change channel announcement into the captured management frame; and re-transmit, via the first wireless interface, the captured management frame including the change channel announcement.
In one example, a computing system is described. The computing system is configured to perform a set of acts that includes obtaining, from a DEP, a non-redacted unique viewer count for a set of digital content exposures. The set of acts also includes obtaining, from the DEP via the protected cloud environment, a redacted exposures count for the set of digital content exposures. In addition, the set of acts includes determining, using an inverted reach curve and the non-redacted unique viewer count, an initial exposures value for the set of digital content exposures. The set of acts also includes scaling the initial exposures value using the redacted exposures count to obtain a final exposures value. Further, the set of acts includes determining, using a reach curve and the final exposures value, a final unique viewer count for the set of digital content exposures, and outputting the final unique viewer count.
Methods, apparatus, systems, and articles of manufacture for user identification via community detection are disclosed. Example instructions, when executed, cause at least one processor to at least access personally identifiable information to device links, build a device graph based on the personally identifiable information to device links, split components of the device graph into person clusters using community detection, create a snapshot including a device-to-person link lookup, and prepare a person-level impression measurement report from the snapshot.
Methods, apparatus, systems and articles of manufacture are disclosed for associating different watermarks detected in media. An example method disclosed herein includes determining whether a first watermark detected in a media signal is represented in a watermark data structure and associating the first watermark with a first media presentation record associated with a second watermark in response to the first watermark being associated in the watermark data structure with the second watermark. The example method further includes transmitting monitoring data including the first media presentation record to an audience measurement entity.
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
G06F 21/16 - Program or content traceability, e.g. by watermarking
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/845 - Structuring of content, e.g. decomposing content into time segments
A cover song identification method implemented by a computing system comprises receiving, by a computing system and from a user device, harmonic pitch class profile (HPCP) information that specifies one or more HPCP features associated with target audio content. A major chord profile feature and a minor chord profile feature associated with the target audio content are derived from the HPCP features. Machine learning logic of the computing system determines, based on the major chord profile feature and the minor chord profile feature, a relatedness between the target audio content and each of a plurality of audio content items specified in records of a database. Each audio content item is associated with cover song information. Cover song information associated with an audio content item having a highest relatedness to the target audio content is communicated to the user device.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Systems and methods are disclosed for dynamic content delivery based on vehicle navigational attributes. An example apparatus includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to at least obtain navigational attributes from an electronic device of a vehicle via a network, determine a relevancy score for respective ones of first sporting event data items based on the navigational attributes, based on a determination that the navigational attributes correspond to a driving condition, identify a second sporting event data item of the first sporting event data items based on a relevancy score of the second sporting event data item corresponding to the driving condition, and transmit the second sporting event data item to the electronic device of the vehicle to cause the second sporting event data item to be presented.
G01C 21/26 - NavigationNavigational instruments not provided for in groups specially adapted for navigation in a road network
B60W 40/08 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to drivers or passengers
G01C 21/36 - Input/output arrangements for on-board computers
G06F 16/2457 - Query processing with adaptation to user needs
G06F 16/9535 - Search customisation based on user profiles and personalisation
G06F 16/9537 - Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
H04L 67/12 - Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Methods, apparatus, systems and articles of manufacture are disclosed to optimize reference signature matching using watermark matching. An example disclosed herein includes selecting first unhashed reference signatures to evaluate for a second time segment of monitoring data based on watermark coverage of a first time segment of the monitoring data, the monitoring data obtained from a meter monitoring media presented by a media device and comparing the first unhashed reference signatures with first unhashed monitored signatures from the second time segment of the monitoring data. The example further includes, when a first media event associated with the monitoring data is not identifiable based on the comparing of the first of unhashed reference signatures with the first unhashed monitored signatures hashing the first unhashed monitored signatures to form a corresponding first hashed monitored signatures and comparing the first hashed monitored signatures with a library of reference hashed signatures to determine the first media event associated with the second time segment of the monitoring data.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/8358 - Generation of protective data, e.g. certificates involving watermark
Methods and apparatus disclosed herein can be used to perform co-viewer adjustment. An example apparatus or viewership adjustment includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to determine compliant and non-compliant household panel meter data based on household metrics for past household viewing behavior, adjust undercounted viewership data based on an active media session interval associated with the household metrics, adjust overcounted viewership data based on a viewership model, the viewership model trained using the compliant household panel meter data, and output adjusted viewership data based on the adjusted undercounted viewership data and adjusted overcounted viewership data.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/466 - Learning process for intelligent management, e.g. learning user preferences for recommending movies
83.
Compensating for Time Scale Differences between Audio and Other Signals in Fingerprinting and Matching Applications
A method includes receiving, by a computing system, an audio signal, where the audio signal defines a segment of media content over time. The method also includes establishing by the computing system, based on the received audio signal, a normalized query frequency-domain representation of the received audio signal. The method further includes matching, by the computing system, the normalized query frequency-domain representation of the received audio signal with a correspondingly normalized reference frequency-domain representation of a reference audio signal having an associated identity. The method additionally includes based on the matching, determining by the computing system that an identity of the received audio signal is the associated identity of the reference audio signal.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Methods, apparatus, systems and articles of manufacture are disclosed to identify media that has been pitch shifted, time shifted, and/or resampled. An example apparatus includes: memory; instructions in the apparatus; and processor circuitry to execute the instructions to: transmit a fingerprint of an audio signal and adjusting instructions to a central facility to facilitate a query, the adjusting instructions identifying at least one of a pitch shift, a time shift, or a resample ratio; obtain a response including an identifier for the audio signal and information corresponding to how the audio signal was adjusted; and change the adjusting instructions based on the information.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Methods, apparatus, systems and articles of manufacture are disclosed for dynamic volume adjustment via audio classification. Example apparatus include at least one memory; instructions; and at least one processor to execute the instructions to: analyze, with a neural network, a parameter of an audio signal associated with a first volume level to determine a classification group associated with the audio signal; determine an input volume of the audio signal; determine a classification gain value based on the classification group; determine an intermediate gain value as an intermediate between the input volume and the classification gain value by applying a first weight to the input volume and a second weight to the classification gain value; apply the intermediate gain value to the audio signal, the intermediate gain value to modify the first volume level to a second volume level; and apply a compression value to the audio signal, the compression value to modify the second volume level to a third volume level that satisfies a target volume threshold.
G10L 25/30 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the analysis technique using neural networks
G10L 25/51 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination
86.
METHODS AND APPARATUS TO DETERMINE A NUMBER OF PEOPLE IN AN AREA
Methods, apparatus, systems and articles of manufacture are disclosed to determine the number of people at a location. An example apparatus includes a configuration changer to change a configuration setting of the base station to cause mobile devices to register with the base station, a registration manager to respond to registration requests received from the mobile devices after the configuration setting is changed by storing device identification information for the corresponding mobile devices, and a counter controller to identify a number of the mobile devices at a location of the base station based on the stored device identification information.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04L 43/0876 - Network utilisation, e.g. volume of load or congestion level
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
H04W 4/00 - Services specially adapted for wireless communication networksFacilities therefor
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
H04W 4/029 - Location-based management or tracking services
H04W 12/00 - Security arrangementsAuthenticationProtecting privacy or anonymity
Example systems and methods for automated generation of banner images are disclosed. A program identifier associated with a particular media program may be received by a system, and used for accessing a set of iconic digital images and corresponding metadata associated with the particular media program. The system may select a particular iconic digital image for placing a banner of text associated with the particular media program, by applying an analytical model of banner-placement criteria to the iconic digital images. The system may apply another analytical model for banner generation to the particular iconic image to determine (i) dimensions and placement of a bounding box for containing the text, (ii) segmentation of the text for display within the bounding box, and (iii) selection of font, text size, and font color for display of the text. The system may store the particular iconic digital image and banner metadata specifying the banner.
An example method may include receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program. A computer-implemented automated face recognition program may be applied to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image, together with respective geometric coordinates for each of the one or more detected faces. At least a subset of the prior-determined set of feature vectors may be associated with a respective one of the particular people. The digital image together may be stored in non-transitory computer-readable memory, together with information assigning respective identities of the recognized particular people, and associating with each respective assigned identity geometric coordinates in the digital image.
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
89.
SELECTING BALANCED CLUSTERS OF DESCRIPTIVE VECTORS
A clustering machine can cluster descriptive vectors in a balanced manner. The clustering machine calculates distances between pairs of descriptive vectors and generates clusters of vectors arranged in a hierarchy. The clustering machine determines centroid vectors of the clusters, such that each cluster is represented by its corresponding centroid vector. The clustering machine calculates a sum of inter-cluster vector distances between pairs of centroid vectors, as well as a sum of intra-cluster vector distances between pairs of vectors in the clusters. The clustering machine calculates multiple scores of the hierarchy by varying a scalar and calculating a separate score for each scalar. The calculation of each score is based on the two sums previously calculated for the hierarchy. The clustering machine may select or otherwise identify a balanced subset of the hierarchy by finding an extremum in the calculated scores.
Methods, apparatus, systems and articles of manufacture are disclosed to identify media. An example method includes: in response to a query, generating an adjusted sample media fingerprint by applying an adjustment to a sample media fingerprint; comparing the adjusted sample media fingerprint to a reference media fingerprint; and in response to the adjusted sample media fingerprint matching the reference media fingerprint, transmitting information associated with the reference media fingerprint and the adjustment.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Methods, apparatus, systems, and articles of manufacture are disclosed herein to identify media presentation by analyzing network traffic. Example instructions cause a machine to generate a traffic profile to reduce a computational burden of identifying streaming media being presented on a media presentation device, the traffic profile including first network traffic data indicative of the streaming media; obtain the traffic profile and second network traffic data corresponding to the streaming media; and generate, in response to a score for the second network traffic data meeting a threshold of similarity, a network traffic analysis report identifying the streaming media being presented on the media presentation device.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04H 60/29 - Arrangements for monitoring broadcast services or broadcast-related services
H04L 41/50 - Network service management, e.g. ensuring proper service fulfilment according to agreements
H04N 21/233 - Processing of audio elementary streams
H04N 21/234 - Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
H04N 21/24 - Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth or upstream requests
H04N 21/647 - Control signaling between network components and server or clientsNetwork processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load or bridging between two different networks, e.g. between IP and wireless
Example apparatus disclosed herein includes a grouper to generate a first presence indication based on a threshold number of segments of image data including patterns of light values corresponding to a first human pulse. Disclosed example apparatus also include a face identifier to identify a first location associated with a human face in an environment associated with the image data based on thermal imaging data from a thermal imaging device, and output the first location associated with the human face in the environment associated with the image data.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
G06V 10/143 - Sensing or illuminating at different wavelengths
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
H04H 60/33 - Arrangements for monitoring the users' behaviour or opinions
H04H 60/45 - Arrangements for identifying or recognising characteristics with a direct linkage to broadcast information or to broadcast space-time, e.g. for identifying broadcast stations or for identifying users for identifying users
H04N 21/258 - Client or end-user data management, e.g. managing client capabilities, user preferences or demographics or processing of multiple end-users preferences to derive collaborative data
Methods, apparatus, systems and articles of manufacture are disclosed for scalable architectures for reference signature matching and updating. An example method for scalable architectures for reference signature matching and updating includes accessing site signatures to be compared to reference signatures from a first group of media sources. Determining if a first reference node is an owner of a first one of the site signatures. Comparing a neighborhood of site signatures including the first site signature to reference signatures in a first subset of reference signatures when the first reference node is the owner of the first site signature, the first subset of references signatures stored in a first memory partition associated with the first reference node. Not comparing site signature to reference signatures when the first reference node is not the owner of the first one of the site signatures.
G06F 16/683 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06F 16/783 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
G06V 10/40 - Extraction of image or video features
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
G06V 10/94 - Hardware or software architectures specially adapted for image or video understanding
G06V 10/96 - Management of image or video recognition tasks
94.
METHODS AND APPARATUS TO IMPUTE MEDIA CONSUMPTION BEHAVIOR
Methods, apparatus, systems and articles of manufacture to impute media consumption behavior are disclosed. An example system includes one or more media meters to obtain tuning data, one or more people meters to obtain viewing data, and one or more servers to, in response to a determination that a difference satisfies a first threshold, determine that a first subset of the tuning data associated with first panelist households having tuned to first media in a first area exhibits local bias, determine that a second subset of the viewing data associated with second panelist households having viewed the first media in the second area represents heavy viewing, and impute the second subset of the viewing data for the first subset of the tuning data in response to the second subset of the viewing data representing heavy viewing.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
H04N 21/45 - Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies or resolving scheduling conflicts
H04N 21/84 - Generation or processing of descriptive data, e.g. content descriptors
95.
METHODS AND APPARATUS TO COMPENSATE FOR SERVER-GENERATED ERRORS IN DATABASE PROPRIETOR IMPRESSION DATA DUE TO MISATTRIBUTION AND/OR NON-COVERAGE
Methods and apparatus to compensate impression data for misattribution and non-coverage are disclosed. An example method includes receiving a first request from a first type of computing device; sending a request for demographic information corresponding to requests received at a first internet domain from the first type of computing device; generating an aggregated audience distribution including a first audience distribution of a first household aggregated with a second audience distribution of a second household; normalizing the aggregated audience distribution to generate a misattribution correction matrix, the misattribution correction matrix including a probability that an impression of the media is attributable to a first demographic group when the database proprietor determines the impression corresponds to a person in a second demographic group; and compensating misattribution error in the impressions by re-assigning the impressions from the second demographic group to the first demographic group using the misattribution correction matrix.
G06Q 30/0242 - Determining effectiveness of advertisements
H04W 4/18 - Information format or content conversion, e.g. adaptation by the network of the transmitted or received information for the purpose of wireless delivery to users or terminals
H04W 4/21 - Services signallingAuxiliary data signalling, i.e. transmitting data via a non-traffic channel for social networking applications
96.
MEDIA STREAMS WITH A WIRELESS ISOCHRONOUS DATA LINK
Methods, apparatus, systems, and articles of manufacture are disclosed to measure audience exposure to media streams with a wireless isochronous data link. In one example, an apparatus includes a datastore, a network interface circuitry, and processor circuitry. The network interface circuitry obtains a first copy of audio data from a first wireless data link, the audio data transmitted from an audio source device, wherein a second copy of the audio data is transmitted, synchronously to the first copy of the audio data, to an audio sink device over a second wireless data link. The processor circuitry to instantiate data parsing circuitry to parse a media stream identifier from the first copy of the audio data and media identification assignment circuitry to assign the media stream identifier to an audio data log for the audio sink device.
H04N 21/442 - Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed or the storage space available from the internal hard disk
Methods, apparatus, systems and articles of manufacture are disclosed to improve detection of audio signatures. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: determine a first time difference of arrival for a first audio sensor of a meter and a second audio sensor of the meter based on a first audio recording from the first audio sensor and a second audio recording from the second audio sensor; determine a second time difference of arrival for the first audio sensor and a third audio sensor of the meter based on the first audio recording and a third audio recording from the third audio sensor; determine a match by comparing the first time difference of arrival to i) a first virtual source time difference of arrival and ii) a second virtual source time difference of arrival; in response to determining that the first time difference of arrival matches the first virtual source time difference of arrival, identify a first virtual source location as the location of a media presentation device presenting media; and remove the second audio recording to reduce a computational burden on the processor.
G01S 5/22 - Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
G01S 5/24 - Position of single direction-finder fixed by determining direction of a plurality of spaced sources of known location
H04R 1/40 - Arrangements for obtaining desired frequency or directional characteristics for obtaining desired directional characteristic only by combining a number of identical transducers
Methods and apparatus to extract a pitch-independent timbre attribute from a media signal are disclosed. An example apparatus includes an audio characteristic extractor to determine a logarithmic spectrum of an audio signal; transform the logarithmic spectrum of the audio signal into a frequency domain to generate a transform output; determine a magnitude of the transform output; and determine a timbre attribute of the audio signal based on an inverse transform of the magnitude.
G10H 3/12 - Instruments in which the tones are generated by electromechanical means using mechanical resonant generators, e.g. strings or percussion instruments, the tones of which are picked up by electromechanical transducers, the electrical signals being further manipulated or amplified and subsequently converted to sound by a loudspeaker or equivalent device
G10H 1/06 - Circuits for establishing the harmonic content of tones
Example methods and systems for indexing fingerprints are described. Fingerprints may be made up of sub-fingerprints, each of which corresponds to a frame of the media, which is a smaller unit of time than the fingerprint. In some example embodiments, multiple passes are performed. For example, a first pass may be performed that compares the sub-fingerprints of the query fingerprint with every thirty-second sub-fingerprint of the reference material to identify likely matches. In this example, a second pass is performed that compares the sub-fingerprints of the query fingerprint with every fourth sub-fingerprint of the likely matches to provide a greater degree of confidence. A third pass may be performed that uses every sub-fingerprint of the most likely matches, to help distinguish between similar references or to identify with greater precision the timing of the match. Each of these passes is amenable to parallelization.
Methods, apparatus, systems and articles of manufacture are disclosed to monitor streaming media. An example apparatus includes memory, instructions in the apparatus, and processor circuitry to execute the instructions to: calibrate video data based on audio data, the video data and the audio data associated with a media stream, generate a signature representative of the media stream based on the calibrated video data, compare the signature to a signature database to identify a matching signature in the signature database; and credit media corresponding to the matching signature as being viewed.
H04L 65/65 - Network streaming protocols, e.g. real-time transport protocol [RTP] or real-time control protocol [RTCP]
H04N 21/2662 - Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities