Analysis of Robust Background Modeling Techniques for Different Information Levels
WANG Zhi-Ling1, ZHOU Lu-Ping1, CHEN Zong-Hai1,2
1.MOE-MS Key Laboratory of Multimedia Calculation and Communication, Department of Automation, University of Science and Technology of China, Hefei 230027 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080
Abstract:Background modeling is a critical element of detecting and tracking moving objects, and the robustness problem of the background model attracts more and more attention. Firstly, the requirements for robustness are analyzed by taking two aspects into account: different applications/environments and different modalities of sampling sets. Then, a review of current background modeling algorithms and systems is presented according to their information levels and performance. After analyzing these algorithms and comparing typical background modeling systems, several promising directions of background modeling are pointed out for future research.
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