Qin Mingxin

Moving objects extraction method in H.264/advanced video coding bit stream of a complex scene

For the purpose of extracting moving objects from H.264/advanced video coding (AVC) bit stream of a complex scene, an algorithm based on maximum a posteriori Markov random field (MRF) framework to extract moving objects directly from H.264 compressed video is proposed in this paper. It mainly involves encoding information of motion vectors (MVs) and block partition modes in H.264/AVC bit stream and utilizes temporal continuity and spatial consistency of moving object’s pieces. First, it retrieves MVs and block partition modes of identical 4×4 pixel blocks in P frames and establishes Gaussian mixture model (GMM) of the phase of MVs as a reference background, and then creates MRF model based on MVs, block partition modes, the GMM of the background, spatial, and temporal consistency. The moving objects are retrieved by solving the MRF model. The experimental results show that it can perform robustly in a complex environment and the precision and recall have been improved over the existing algorithm.