Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding.

Abstract: Methods and apparatus to identify an emotion evoked by media are disclosed. An example apparatus includes a synthesizer to generate a first synthesized sample based on a pre-verbal utterance associated with a first emotion. A feature extractor is to identify a first value of a first feature of the first synthesized sample. The feature extractor to identify a second value of the first feature of first media evoking an unknown emotion. A classification engine is to create a model based on the first feature. The model is to establish a relationship between the first value of the first feature and the first emotion. The classification engine is to identify the first media as evoking the first emotion when the model indicates that the second value corresponds to the first value.

Abstract: Methods and apparatus to count people are disclosed. Example apparatus disclosed herein include means for discarding existing characteristic datasets from a list; means for populating the list with first characteristic datasets obtained from a first plurality of images representative of an environment during a first period of time of a media presentation; means for limiting a number of the first characteristic datasets stored in the list for a first location represented in the first plurality of images; and means for comparing the first characteristic datasets to each other to determine a first number of unique faces in the environment during the first period of time, wherein the means for discarding is to delete the first characteristic datasets from the list, and the means for populating is to re-populate the list with second characteristic datasets obtained from a second plurality of images representative of the environment.

Abstract: Example apparatus disclosed herein include a memory and a processor to execute instructions to identify a first set of face rectangles and a second set of face rectangles in a frame pair of image data corresponding to a media environment, the first set of face rectangles corresponding to a first image sensor and the second set of face rectangles corresponding to a second image sensor, remove first face rectangles from the first set of face rectangles and the second set of face rectangles when the first face rectangles are determined to correspond to false positive face detections, group second face rectangles that remain in the first set of face rectangles and the second set of face rectangles after removal of the first face rectangles to form groups of face rectangles, and generate a count of people identified in the media environment based on a number of the groups.

Abstract: Methods and apparatus to count people are disclosed. Example people counting apparatus disclosed herein include a difference calculator to calculate a degree of similarity between a first characteristic dataset and a second characteristic dataset representative of face detections in images. Disclosed example people counting apparatus also include a limiter to store the first characteristic dataset and the second characteristic dataset in a plurality of characteristic datasets associated when the degree of similarity does not satisfy a threshold, and to store the first characteristic dataset in the plurality of characteristic datasets and discard the second characteristic dataset when the degree of similarity satisfies the threshold to limit a number of stored characteristic datasets. Disclosed example people counting apparatus further include a comparator to compare the plurality of characteristic datasets to each other to determine a number of unique faces in an environment during a first period of time.

Abstract: Methods and apparatus to present supplemental media on a second screen are disclosed. An example method includes establishing a connection between a digital media device and a computing device based on information identifying the computing device and, in response to establishing the connection, receiving, at the computing device, a first notification from the digital media device including a location of supplemental media; accessing the supplemental media; and in response to accessing the supplemental media, sending a second notification that the supplemental media has been accessed, the second notification to enable media skipping on the digital media device.

Abstract: Example apparatus disclosed herein include an analyzer to determine whether a first face rectangle is located in an overlap region of an image frame pair including a first image frame obtained from a first image sensor and a second image frame obtained from a second image sensor, the first face rectangle associated with the first image frame. Disclosed example apparatus also include a comparator to determine whether the first face rectangle is redundant to a second face rectangle when the first face rectangle is located in the overlap region of the image frame pair. Disclosed example apparatus further include an overlap eliminator to link first coordinates of the first face rectangle and second coordinates of the second face rectangle in a correlated face history when the first face rectangle is redundant to the second face rectangle, the correlated face history to identify redundant face rectangles in subsequent image frame pairs.

Abstract: Methods and apparatus to identify an emotion evoked by media are disclosed. An example apparatus includes a synthesizer to generate a first synthesized sample based on a pre-verbal utterance associated with a first emotion. A feature extractor is to identify a first value of a first feature of the first synthesized sample. The feature extractor to identify a second value of the first feature of first media evoking an unknown emotion. A classification engine is to create a model based on the first feature. The model is to establish a relationship between the first value of the first feature and the first emotion. The classification engine is to identify the first media as evoking the first emotion when the model indicates that the second value corresponds to the first value.

Abstract: Methods, apparatus, systems and articles of manufacture to count people in an audience are disclosed. An apparatus includes a location determiner to determine a location of a portable device was outside of a media exposure environment, and a proximity determiner to determine a person was in proximity to the portable device. The apparatus also includes a presence detector to: generate first presence information based on the location of the portable device and the proximity of the person to the portable device, the first presence information to indicate that the person was absent from the media exposure environment; compare the first presence information to second presence information collected by a people meter; and, when the second presence information indicates the person was present in the media exposure environment, modify the second presence information based on the first presence information.

Abstract: Methods and apparatus to count people are disclosed. Example people counting apparatus disclosed herein include a difference calculator to calculate a degree of similarity between a first characteristic dataset and a second characteristic dataset representative of face detections in images. Disclosed example people counting apparatus also include a limiter to store the first characteristic dataset and the second characteristic dataset in a plurality of characteristic datasets associated when the degree of similarity does not satisfy a threshold, and to store the first characteristic dataset in the plurality of characteristic datasets and discard the second characteristic dataset when the degree of similarity satisfies the threshold to limit a number of stored characteristic datasets. Disclosed example people counting apparatus further include a comparator to compare the plurality of characteristic datasets to each other to determine a number of unique faces in an environment during a first period of time.

Abstract: Methods, apparatus, systems and articles of manufacture to count people in an audience are disclosed. An example system includes means for transmitting a control signal to a portable device a threshold period of time after a person logs into a people meter separate from the portable device. The control signal causes the portable device to begin collecting location information and proximity information. The system also includes means for analyzing the location information to determine a location result indicative of a location of the portable device. The system further includes means for analyzing the proximity information to determine a proximity result indicative of whether the person is near the portable device. The location result and the proximity result collectively define first presence information. The first presence information indicative of whether the person is present in a media exposure environment associated with a media presentation device.

Abstract: Methods and apparatus to count people are disclosed. Example people counting apparatus disclosed herein include a difference calculator to calculate a degree of similarity between a first characteristic dataset and a second characteristic dataset representative of face detections in images. Disclosed example people counting apparatus also include a limiter to store the first characteristic dataset and the second characteristic dataset in a plurality of characteristic datasets associated when the degree of similarity does not satisfy a threshold, and to store the first characteristic dataset in the plurality of characteristic datasets and discard the second characteristic dataset when the degree of similarity satisfies the threshold to limit a number of stored characteristic datasets. Disclosed example people counting apparatus further include a comparator to compare the plurality of characteristic datasets to each other to determine a number of unique faces in an environment during a first period of time.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to utilize audio watermarking for people monitoring are disclosed. Example people monitoring methods disclosed herein include determining, at a user device, whether a first trigger condition for emitting an audio watermark identifying at least one of the user device or a user of the user device is satisfied. Such example methods also include, in response to determining that the first trigger condition is satisfied, providing a first audio signal including the audio watermark to an audio circuit that is to output an acoustic signal from the user device.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to utilize audio watermarking for people monitoring are disclosed. Example people monitoring methods disclosed herein include determining, at a user device, whether a first trigger condition for emitting an audio watermark identifying at least one of the user device or a user of the user device is satisfied. Such example methods also include, in response to determining that the first trigger condition is satisfied, providing a first audio signal including the audio watermark to an audio circuit that is to output an acoustic signal from the user device.

Abstract: Example apparatus disclosed herein include an analyzer to determine whether a first face rectangle is located in an overlap region of an image frame pair including a first image frame obtained from a first image sensor and a second image frame obtained from a second image sensor, the first face rectangle associated with the first image frame. Disclosed example apparatus also include a comparator to determine whether the first face rectangle is redundant to a second face rectangle when the first face rectangle is located in the overlap region of the image frame pair. Disclosed example apparatus further include an overlap eliminator to link first coordinates of the first face rectangle and second coordinates of the second face rectangle in a correlated face history when the first face rectangle is redundant to the second face rectangle, the correlated face history to identify redundant face rectangles in subsequent image frame pairs.

Abstract: Methods and apparatus to determine a blob people count in images are disclosed. An example method includes forming blobs based on whitened pixels of detected face rectangles in pairs of frames of a plurality of image frame captured over a period of time. The method further calculates locations of the centers of the blobs in each frame of the first one of the pairs of frames. The method further eliminates blobs in a first frame of the first one of the pairs of frames having locations within one or more blobs in the second frame of the first one of the pairs of frames. The method further adds the number of remaining blobs from the first frame to the number of blobs in the second frame of the first one of the pairs of frames to form a blob people count.

Abstract: Methods and apparatus to count people are disclosed. Example people counting apparatus disclosed herein include a difference calculator to calculate a degree of similarity between a first characteristic dataset and a second characteristic dataset representative of face detections in images. Disclosed example people counting apparatus also include a limiter to store the first characteristic dataset and the second characteristic dataset in a plurality of characteristic datasets associated when the degree of similarity does not satisfy a threshold, and to store the first characteristic dataset in the plurality of characteristic datasets and discard the second characteristic dataset when the degree of similarity satisfies the threshold to limit a number of stored characteristic datasets. Disclosed example people counting apparatus further include a comparator to compare the plurality of characteristic datasets to each other to determine a number of unique faces in an environment during a first period of time.

Abstract: Methods, apparatus, systems and articles of manufacture to count people in an audience are disclosed. An example system includes means for transmitting a control signal to a portable device a threshold period of time after a person logs into a people meter separate from the portable device. The control signal causes the portable device to begin collecting location information and proximity information. The system also includes means for analyzing the location information to determine a location result indicative of a location of the portable device. The system further includes means for analyzing the proximity information to determine a proximity result indicative of whether the person is near the portable device. The location result and the proximity result collectively define first presence information. The first presence information indicative of whether the person is present in a media exposure environment associated with a media presentation device.

Abstract: Methods and apparatus to count people are disclosed. An example apparatus includes a populator to populate a list with first characteristic datasets obtained from first image data representative of an environment during a first period of time, respective ones of the first characteristic datasets representative of a face detected in the environment during the first period of time; a comparator to compare the first characteristic datasets to each other to determine a first number of unique faces in the environment during the first period of time; and a discarder to delete the first characteristic datasets from the list when the first period of time has ended, the populator to re-populate the list with second characteristic datasets obtained from second image data representative of the environment during a second period of time subsequent to the first period of time.

Abstract: Methods, apparatus, systems and articles of manufacture to count people in an audience are disclosed. An example method includes analyzing location information collected by a portable device indicative of a location of the portable device. The method also includes analyzing proximity information collected by the portable device indicative of when a person is near the portable device. The example method further includes generating presence information based on (1) the location information and (2) the proximity information, the presence information being indicative of whether the person is present in a media exposure environment associated with a media presentation device.