Compressed Domain Motion Analysis for Video Semantic Events Detection
In this paper, a novel approach is proposed to estimate camera motion and segment moving objects from compressed video streams, aiming to detect semantic events in video clips. Simultaneously using the motion vectors and DC components of MPEG macroblocks (MB), the camera motion type and motion parameters of each frame are estimated with simplified models. Then the segmentation of moving objects is done at macroblock level. Exploring the variation of motion information in consecutive frame sequence, a composite feature can be formed to detect semantic events. The experiment results on TRECVID video corpus show that our approach is very effective and efficient.
compressed domain motion analysis object segmentation semantic event mpeg
Run Tao Shouxun Lin Yongdong Zhang
Graduate School of Chinese Academy of Sciences Beijing, China Institute of Computing Technology Chinese Academy of Sciences Beijing, China
国际会议
2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)
太原
英文
201-204
2009-07-10（万方平台首次上网日期，不代表论文的发表时间）