Recently, background modeling and sparse representation methods have been used successfully in video surveillance [14,16]. In Ref [13] background subtracted images are recovered using compressive sensing (CS). Work of Ref [17] proposed the use of principle component pursuit method to detect foreground changes in video surveillance. The work is based on low-rank and sparse decomposition of image matrices. Robust principal component analysis has applications in
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