The Nielsen Comapny (US), LLC

Nielsen Consumer LLC

The Nielson Company (US), LLC

The Neilsen Company (US), LLC

Padmanabhan Soundararajan

Venugopal Srinivasan

Alexander Pavlovich Topchy

Marko Usaj

Robert T Knight

Anantha K Pradeep

Ramachandran Gurumoorthy

Ratnakar Dev

Jose Javier Yebes Torres

Kannan Shanmuganathan

Hussain Masthan

Raju Kumar Allam

Disclosed example people monitoring methods include detecting a first watermark in a first audio signal obtained from an acoustic sensor, the first watermark identifying media presented by a monitored media device, determining whether a second watermark, different from the first watermark, is embedded in the first audio signal obtained from the acoustic sensor, the second watermark identifying at least one of a mobile device or a user of the mobile device, classifying the second watermark as a media watermark or a people monitoring watermark based on a characteristic of the second watermark, and when the second watermark is determined to be embedded in the first audio signal, reporting at least one of the second watermark or information decoded from the second watermark to identify at least one of the mobile device or the user of the mobile device as being exposed to the media presented by the monitored media device.

Audio watermarking for people monitoring

Example apparatus disclosed herein are to determine a location of a portable device based on location data collected by the portable device, determine whether a person is within a threshold distance of the portable device based on proximity data collected by the portable device, and, when the person is determined to be within the threshold distance of the portable device: (i) infer at least one of a presence or an absence of the person in a media exposure environment based on the location of the portable device, (ii) determine a confidence level that the person corresponds to a member of the panelist household, and (iii) determine an accuracy of presence information collected by a people meter based on the confidence level and the inference of the at least one of the presence or the absence of the person, the people meter different than the portable device.

Methods and apparatus to count people in an audience

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.

Methods and apparatus to present supplemental media on a second screen

Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus includes processor circuitry to execute instructions to extract text from the receipt image, the text including bounding boxes; associate ones of the bounding boxes to link horizontally related fields of a the receipt image by selecting a first bounding box; identifying first horizontally aligned bounding boxes, the first horizontally aligned bounding boxes to include at least one bounding box of the bounding boxes that is horizontally aligned relative to the first bounding box; adding the first horizontally aligned bounding boxes to a word sync list; and connecting ones of the first horizontally aligned bounding boxes and the first bounding box based on at least one of an amount of the first horizontally aligned bounding boxes in the word sync list and a relationship among the first horizontally aligned bounding boxes and the first bounding box.

Methods, systems, apparatus and articles of manufacture for receipt decoding

Methods and apparatus to count people are disclosed. Example apparatus disclosed herein are to populate a list with first characteristic datasets obtained from a first plurality of images, respective ones of the first characteristic datasets representative of corresponding faces. Disclosed apparatus are also to perform comparisons of the first characteristic datasets to each other to determine a first number of unique faces, the comparisons limited to the first characteristic datasets obtained during the first period of time. Disclosed apparatus are further to delete the first characteristic datasets from the list after the first period of time has ended, and re-populate the list with second characteristic datasets obtained from a second plurality of images representative of the environment during a second period of time of the media presentation, the second period of time subsequent to the first period of time.

Methods and apparatus to count people

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.

Methods and apparatus to count people in images

Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus for processing a receipt associated with a user disclosed herein includes an optical character recognition engine to generate bounding boxes, respective ones of the bounding boxes associated with groups of characters detected in the receipt, the bounding boxes including a first bounding box, a second bounding box and a third bounding box, a word connector to connect the first bounding box to the second bounding box based on (1) an adjacency of the first bounding box to the second bounding box and (2) a difference value from a comparison of a location of the first bounding box to a location of the second bounding box, a line connector to form a line of the ones of the bounding boxes by connecting the third bounding box to the second bounding based on a relationship between the first bounding box and the second bounding box, the line of the ones of the bounding boxes indicative of related receipt fields, and a creditor to generate a report based on the line.

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.

Methods and apparatus to identify a mood of media

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.

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.

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.

Growing community of inventors

Tampa, FL, United States of America

Padmanabhan Soundararajan