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Video segmentation and camera motion characterization using compressed data

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Published in C.-C. J. Kuo and Shih Fu Chang and Venkat N. Gudivada. Multimedia Storage and Archiving Systems II. Dallas TX. 1997
Collection SPIE Proceedings; 3229
Abstract We address the problem of automatically extracting visual indexes from videos, in order to provide sophisticated access methods to the contents of a video server. We focus on two tasks, namely the decomposition of a video clip into uniform segments (shots) and the characterization of each shot by camera motion parameters. For the first task we use a Bayesian classification approach to detecting scene cuts by analyzing motion vectors. For the second task a least-squares fitting procedure determines the pan/tilt/zoom camera parameters. In order to guarantee the highest processing speed, all techniques process and analyze directly MPEG-1 motion vectors, without need for video decompression. Experimental results are reported for a database of news video clips.
Keywords Dvp, cbirShot detectionCamera motionVideo archivalContent-based retrievnalBayesian classificationMPEG
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Research group Computer Vision and Multimedia Laboratory
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MILANESE, Ruggero, DEGUILLAUME, Frédéric, JACOT-DESCOMBES, Alain. Video segmentation and camera motion characterization using compressed data. In: C.-C. J. Kuo and Shih Fu Chang and Venkat N. Gudivada (Ed.). Multimedia Storage and Archiving Systems II. Dallas TX. [s.l.] : [s.n.], 1997. (SPIE Proceedings; 3229) https://archive-ouverte.unige.ch/unige:47833

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Deposited on : 2015-03-06

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