Paper
10 December 2002 Robust background subtraction in HSV color space
Ming Zhao, Jiajun Bu, Chun Chen
Author Affiliations +
Proceedings Volume 4861, Multimedia Systems and Applications V; (2002) https://doi.org/10.1117/12.456333
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States
Abstract
In the new MPEG-4 video coding standard, automatic video object segmentation plays a key role in supporting object-oriented coding and enabling content-based functionalities. Background subtraction is one of the basic automatic video object segmentation methods. But various environmental illumination conditions often make it hard to work. A robust background subtraction method is presented in this paper. A statistical background model is first setup in this algorithm. Then the hypothesis testing is applied to the following frames to segment the video objects. The HSV color model is used and its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination conditions. Shadows are detected and a new background update algorithm is also presented based on the observation that the illumination changes are temporal and will not influence all the following frames. All of them contribute to the robustness of the method. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating environments.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ming Zhao, Jiajun Bu, and Chun Chen "Robust background subtraction in HSV color space", Proc. SPIE 4861, Multimedia Systems and Applications V, (10 December 2002); https://doi.org/10.1117/12.456333
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Cited by 35 scholarly publications.
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KEYWORDS
Video

RGB color model

Statistical analysis

Statistical modeling

Video coding

Video surveillance

Binary data

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