Titlebook: Video Mining; Azriel Rosenfeld,David Doermann,Daniel DeMenthon Book 2003 Springer Science+Business Media New York 2003 Audio.Frames.inform

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Unsupervised Mining of Statistical Temporal Structures in Video,tive segments in a video stream with consistent statistical characteristics. Such structures can often be interpreted in relation to distinctive semantics, particularly in structured domains like sports. While much work in the literature explores the link between the observations and the semantics u

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Pseudo-Relevance Feedback for Multimedia Retrieval, a text description, audio, still images and/or video sequences. The actual search also takes place in the text, audio, image or video domain. We present an approach that uses pseudo-relevance feedback from retrieved items that are NOT similar to the relevant items. An evaluation on the 2002 TREC Vi

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1571-5205 me to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, comp

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