Abstract：An algorithm is proposed to segment foreground accurately from videos whose background is dynamic or whose foreground performs non-translational motion. Firstly, by regarding the change process of a single pixel as discrete-time signal, the video is segmented into foreground and background in a glancing way with temporal analysis using Gabor filter. Secondly, global color model and local color model are defined and built by clustering the color information of the background and foreground with mean-shift algorithm. Finally, a double-labeling method is used for fine segmentation of the foreground. Experimental results on several datasets prove that the proposed algorithm evidently improves the precision of the extracted foreground, especially in the cases that the background is dynamic or the foreground performs non-translational motion.
闵华清，陈聪，罗荣华，朱金辉. 基于时空分析的视频前景提取[J]. 模式识别与人工智能, 2011, 24(4): 582-590.
Ming Hua-Qing, Chen Cong, Luo Rong-Hua, Zhu Jin-Hui. Video Foreground Segmentation Based on Analysis of Spatial-Temporal Information. , 2011, 24(4): 582-590.
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