Paper
6 October 1997 Video segmentation and camera motion characterization using compressed data
Ruggero Milanese, Frederic Deguillaume, Alain Jacot-Descombes
Author Affiliations +
Proceedings Volume 3229, Multimedia Storage and Archiving Systems II; (1997) https://doi.org/10.1117/12.290367
Event: Voice, Video, and Data Communications, 1997, Dallas, TX, United States
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 tow tasks, namely the decomposition of a video clip into uniform segments, 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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ruggero Milanese, Frederic Deguillaume, and Alain Jacot-Descombes "Video segmentation and camera motion characterization using compressed data", Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); https://doi.org/10.1117/12.290367
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Cited by 19 scholarly publications.
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KEYWORDS
Cameras

Video

Motion analysis

Zoom lenses

Video compression

Databases

Motion models

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