Abstract
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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
