Video segmentation and camera motion characterization using compressed data | Zendy

Ruggero Milanese | Zendy; F. Deguillaume | Zendy; Alain Jacot-Descombes | Zendy

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<title>Video segmentation and camera motion characterization using compressed data</title>

Author(s) -

Ruggero Milanese,

F. Deguillaume,

Alain Jacot-Descombes

Publication year - 1997

Publication title -

proceedings of spie, the international society for optical engineering/proceedings of spie

Language(s) - English

Resource type - Conference proceedings

SCImago Journal Rank - 0.192

H-Index - 176

eISSN - 1996-756X

pISSN - 0277-786X

DOI - 10.1117/12.290367

Subject(s) - computer science , artificial intelligence , computer vision , motion compensation , zoom , motion estimation , segmentation , shot (pellet) , motion (physics) , focus (optics) , block matching algorithm , video tracking , computer graphics (images) , video processing , chemistry , physics , organic chemistry , optics , petroleum engineering , engineering , lens (geology)

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.

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