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Proceedings Paper

An improved background subtraction approach in target detection and tracking
Author(s): Hao Lai; Yuesheng Zhu; Zhenming Nong
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Paper Abstract

In this paper, a novel background subtraction approach is proposed to avoid stationary foreground objects being merged into the background in target detection and tracking, in which an improved background model is designed by using virtual frames and the blur can be attenuated with this model when an object moves again after it stays for a long time. Moreover, the proposed model is fused with the eigenbackgrounds to improve the environmental adaptability. Our experimental results indicate that the proposed approach enhances the performance of target detection and tracking in intelligent surveillance and is superior to some state-of-the-art methods according to the precision-recall measurement.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90671S (24 December 2013); doi: 10.1117/12.2052825
Show Author Affiliations
Hao Lai, Peking Univ. (China)
Yuesheng Zhu, Peking Univ. (China)
Zhenming Nong, Peking Univ. (China)

Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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