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subtraction is a basic problem for change detection in videos and also the first step of high-level computer vision applications. Most background subtraction methods rely on color and texture feature. However, due to illuminations changes in different scenes and affections of noise pixels, those methods often resulted in high false positives in a complex environment. To solve this problem, we propose an adaptive background subtraction model which uses a novel Local SVD Binary Pattern (nameddoi:10.1109/cvprw.2016.148 dblp:conf/cvpr/GuoXQ16 fatcat:r7cmnecrkrboneloaq25qemany