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Proceedings Paper

Automatic and robust classification of independent motions in video sequences
Author(s): Xiaobo An; Xueying Qin; Hujun Bao
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Paper Abstract

Segmentation of independent motions from video sequences is a challenging problem that can be a prelude to many further applications in computer vision. In this paper, we present an accurate and efficient approachfor automatic segmentation of all the independently moving objects in the scene. The system begins with an initialization module which provides initial partition of the scene, computes 2D motions, and includes some necessary preparing work. Then, we propose a novel object classification method by analyzing and clustering motions. To achieve the best robustness, and minimize the total computation load, we choose to work on multi key frames simultaneously to obtain global optimal classification. Our approach achieves accurate object classification and avoids the uncertainty in detection of moving objects. We demonstrate high stability, accuracy and performance of our algorithm with a set of experiments on real video sequences.

Paper Details

Date Published: 18 January 2006
PDF: 8 pages
Proc. SPIE 6066, Vision Geometry XIV, 60660B (18 January 2006);
Show Author Affiliations
Xiaobo An, Zhejiang Univ. (China)
Xueying Qin, Zhejiang Univ. (China)
Hujun Bao, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 6066:
Vision Geometry XIV
Longin Jan Latecki; David M. Mount; Angela Y. Wu, Editor(s)

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