关键词: 统计标号, 运动目标提取, 压缩域, 快速平均移聚类

Abstract: A fast moving object extraction method working in MPEG compressed domain is proposed in this paper. The embedded motion vectors and DC coefficients of DCT transformation in an MPEG-like coded video stream are acquired by partially decoding and used as input to the algorithm; the moving object mask for each P frame is extracted. Firstly, the global motion between current frame and the last reference frame is estimated by robust regression analysis, and blocks non-conforming to the estimated global motion are marked as potential moving blocks; Then, taking the upsampled motion vector field as the temporal space feature, and the reconstructed DC image converted to LUV color space as the spatial space feature, a fast mean-shift based clustering procedure is performed to find regions with similar temporal and spatial characteristics and get finer region boundaries; Finally, the moving object mask is obtained by an MRF-based statistical labeling procedure. The experimental results show that the proposed algorithm can effectively suppress the influence of motion vector noises, and have a very fast processing speed (For CIF video streams, the algorithm can run at a speed of 50 frames per second).

Key words: statistical labeling, moving object extraction, compressed domain, fast mean-shift clustering