Detection algorithm of moving objects based on background subtraction method
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摘要: 針對靜止攝像機下的運動目標檢測問題,提出了一種基于背景減法的運動目標檢測算法.首先利用無拘束學習方式迅速建立多個可靠的RGB顏色背景模型,然后在運動目標分割過程中,及時地根據場景變化對背景模型進行更新,同時利用色度信息及局部交叉熵信息去除陰影,得到較為精確的運動目標.在對用普通USB攝像頭獲取的視頻序列實驗中,該算法顯示了良好的性能.Abstract: A detection algorithm of moving objects based on background subtraction method was proposed for a video surveillance system with static camera. Some multi-background models dealing with RGB colors were built during the leaning process without any restraint. The modes can be updated in good time with the change of background during moving object segmentation. Chromatic difference and cross-entropy were employed to eliminate shadows and made the moving object areas more accurate. This algorithm demonstrates better performance in the experiments with video sequences captured by a general USB camera.
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Key words:
- moving object detection /
- background subtraction /
- shadow elimination /
- cross-entropy
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