Abstract：Since dynamic background may be erroneously detected as a moving object in the Robust Principal Component Analysis (RPCA) algorithm, a RPCA-based moving object detection optimization algorithm is proposed to improve it. After detected by the RPCA algorithm, the moving object will be separated from dynamic background according to the Gaussian distribution of dynamic background in the time domain and the difference of mean value and variance between dynamic background and moving object in the whole video stream. The results show that the algorithm can deal with dynamic background effectively and detect the moving objects well.
杨依忠,汪鹏飞,胡雄楼,伍能举. 基于鲁棒主成分分析的运动目标检测优化算法[J]. 电子与信息学报, 2018, 40(6): 1309-1315.
YANG Yizhong, WANG Pengfei, HU Xionglou, WU Nengju. Moving Object Detection Optimization Algorithm Based on Robust Principal Component Analysis. JEIT, 2018, 40(6): 1309-1315.
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