A Real-time H. 264 Compressed Domain Based Moving Object Segmentation Algorithm
基于H．264压缩域的实时运动对象分割算法

Moving object segmentation in the compressed domain is absolutely necessary for real-time applications.Due to the predominant compression efficiency,the emerging video coding standard H.264 is replacing MPEG-2/4 in many multimedia applications,but moving object segmentation in the H.264 compressed domain is rarely investigated until now.In this paper,we present a new approach to segment moving objects from the H.264 compressed domain.The motion vector(MV) field extracted from the H.264 compressed video is first normalized in both temporal and spatial domain,and the MV fields of several continuous frames are accumulated to enhance the salient motion.Then the global motion compensation is performed on the accumulated MV field,while the fast statistical region growing algorithm is exploited to segment it into different motion-homogenous regions.Finally,the orientation histogram of the MV field is exploited to determine the moving object regions.Experimental results for several MPEG-4 test sequences demonstrate the proposed approach can segment moving objects from the H.264 compressed domain in real time,and exhibit good segmentation quality.