Efficient motion segmentation for H.264 compressed video

Abstract

The H.264 standard is a new state-of-the-art video coding standard with extensive applications. This paper presents a simple and efficient approach for motion segmentation in H.264 compressed video. Several preprocessing steps are used before actual motion segmentation. The raw motion vector (MV) field extracted from H.264 video is first spatially normalized and then accumulated by the forward projection scheme to obtain the dense MV field. The following global motion compensation is performed on the accumulated MV field to acquire the residual MV field. Based on the residual MV field, a hybrid scheme including edge detection and region growing for motion segmentation is proposed. The edge map is used as a mask to guide region growing, which is created by Canny operator based on the magnitude map of residual MV field. At last, hypothesis testing as the major postprocessing technique is exploited to distinguish between the background and different moving objects. Experiment results demonstrate that the high-efficiency performance and good segmentation quality of the proposed approach.