Alphonso Inc.

Zhengxiang Pan

Lampros Kalampoukas

Ashish Chordia

Manish Satyapal Gupta

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, categorizing a temporal position of the identified video frames within the commercial as being in either a beginning or ending portion of the commercial, or a middle portion of the commercial, and assigning to the commercial the identified products or brands as primary metadata candidates when the temporal position of the identified video frames within the commercial is in either the beginning or ending portion of the commercial.

Automoted identification of product or brand-related metadata candidates for a commercial using temporal position of product or brand-related text or objects, or the temporal position and audio, in video frames of the commercial

A system and method are provided for detecting the presence of potential commercials in a video data stream. Each of the commercials has an expected time length that is an integer multiple of a first predetermined time length, and has an overall time length that is equal to or less than a second predetermined time length. Transitions in the audio or video of the video data stream are detected and the time of the transitions are recorded. Time differences between one or more successive transitions are detected. Any time differences that are an integer multiple of the first predetermined time length, and that have an overall time length that is equal to or less than the second predetermined time length are identified. The contents of the video data stream associated with the identified time differences are flagged as potential commercials and sent to a content processing platform for further analysis.

Detection of potential commercial by detection and analysis of transitions in video content

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, performing audio analysis on the commercial to identify audio associated with one or more identifiable products or brands in the commercial, comparing the products and brands identified by the image analysis with the products and brands identified by the audio analysis, and identifying similar products and brands; and assigning to the commercial a product or brand as a primary metadata candidate when a similar product or brand is identified by the image analysis and the audio analysis.

Automated identification of product or brand-related metadata candidates for a commercial using consistency between audio and image elements of products or brands detected in commercials

Methods and apparatus are provided for detecting potential repeating content, such as commercials, in a video data stream by receiving one or more video data streams, parsing each video data stream into a plurality of segments, creating audio fingerprints of each segment, storing the plurality of audio fingerprints in a database, and identifying any audio fingerprints in the received and parsed one or more video data streams that match audio fingerprints in the database that were previously stored from video data streams that were previously received and parsed. Video fingerprints are then created for these same pairs of segments and a similarity analysis is performed. The results of the video fingerprint analysis is used to make a determination of subsequent actions to be taken by a content processing platform that performs recognition processing of the content associated with the segments identified as being potentially repeating content.

System and method for detecting repeating content, including commercials, in a video data stream using audio-based and video-based automated content recognition

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, calculating a dominance or prominence metric from the frame data for each of the identifiable product-related logos, brand-related logos, product-related text, or brand-related text, comparing the dominance or prominence metric for each of the identifiable product-related logos, brand-related logos, product-related text, or brand-related text to a predetermined threshold percentage or value, and assigning to the commercial, the identified products or brands as metadata candidates when the dominance or prominence metric exceeds the predetermined threshold percentage or value.

Automated identification of product or brand-related metadata candidates for a commercial using dominance and prominence of product or brand-related text or objects in video frames of the commercial

A method and system are provided for assigning metadata candidates to a commercial by performing image analysis on a plurality of the video frames to identify video frames that include one or more of identifiable product-related logos, brand-related logos, product-related text, or brand-related text which appear in the video frames, capturing frame data for such video frames, calculating a persistence metric from the frame data for each of the identifiable product-related logos, brand-related logos, product-related text, or brand-related text, comparing the persistence metric for each of the identifiable product-related logos, brand-related logos, product-related text, or brand-related text to a predetermined threshold value, and assigning to the commercial, the identified products or brands as metadata candidates when the persistence metric exceeds the predetermined threshold value.

Automated identification of product or brand-related metadata candidates for a commercial using persistence of product or brand-related text or objects in video frames of the commercial

Automated identification of product or brand-related metadata candidates for a commercial using consistency between audio and image elements of products of brands detected in commercials

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Edison, NJ, United States of America

Zhengxiang Pan