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Large Scale Content Analysis Engine

By David Gibbon and Zhu Liu


The evolution of IP video systems has resulted in unprecedented access to a wide range of video material for consumers via IPTV and Web delivery. Retrieval technologies help users find relevant content, but suffer from a paucity of reliable content descriptions. In this paper, we describe the large scale content analysis engine (CAE) which is designed to facilitate content based video retrieval, as well as a number of other applications such as content repurposing, video browsing, discovering content relationships, and fine-grained content personalization. A scalable system is presented to handle video from broadcast, enterprise and web sources for applications including IPTV and mobile video. Media processing includes shot boundary detection, automatic speech recognition, face detection, clustering of shots and faces, speaker segmentation, closed caption alignment, concept detection, and transcoding. Metadata ingest, augmentation and delivery using a standards-based approach enable the CAE to serve a range of content processing applications

Topics: Algorithms, Management, Performance, Human Factors. Keywords Multimedia content analysis, content ingestion, content adaptation, metadata, transcoding
Year: 2011
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