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Abstract

A content segmentation, categorization and identification method on consumer devices (clients) is described. Methods for content tracking are illustrated that are suitable for large scale deployment and applications such as broadcast monitoring, novel content publishing and interaction. Time-aligned (synchronous) applications such as multi-language selection, customized advertisements, second screen services and content monitoring applications can be economically deployed at large scales. The client performs fingerprinting, scene change detection, audio turn detection, and logo detection on incoming video and gathers database search results, logos and text to identify and segment video streams into content, promos, and commercials. A learning engine is configured to learn rules for optimal identification and segmentation at each client for each channel and program. Content sensed at the client site is tracked with reduced computation and applications are executed with timing precision. A method and user interface for time-aligned publishing of content and subsequent usage and interaction on one or more displays is described.

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