Moving Object Detection in Compressed Domain for High Resolution Videos
Minh Hoa Nguyen, Tung Long Vuong, Dinh Nam Nguyen, Do Van Nguyen, Lê Thanh Hà, Thi Thuy Nguyen · 2017
Motion detection in pixel domain of videos often requires highly capable resource to perform. This is due to computational demands for decoding the videos to obtain visual image. The problem can be solved by performing motion detection directly on bit streams of the compressed video data. This paper presents a new method for moving object detection in compressed domain of high resolution surveillance videos. In this work, we use video coding parameters (eg. motion vectors) extracted directly from bit stream of the compressed video to separate the moving blocks out of video background. We then propose new techniques for the segmentation and refinement of the foreground blocks to detect the moving objects. Experiments have been conducted on both public and self-recorded video data sets. Experimental results show the outperformance of our proposed method in comparing with conventional one.