Abstract:

Moving objects detection for video processing,which focuses on dividing video images into foreground and background,is important in computer vision.We analyze several traditional moving detection methods,and propose a dynamically updating projection method for online moving objects detection.The proposed method uses the low rank representation (LRR) method to obtain the low rank part of several continuous video images,and thus the projection can be constructed with orthogonal complement of the left singular matrix from the obtained low rank part.The sparse foreground can be obtained by solving the projection model.Besides,the video can be divided into several uniformlyspaced parts,based on which the projection can be dynamically updated.Experimental results on several video databases such as the Curtain demonstrate that our method has better detection performance than the other methods,and it has strong robustness especially when dealing with dynamic background and complex foreground.

Key words: low rank representation, projection matrix, online moving objects detection