Conference Paper
RealTime Foreground Segmentation for the Moving Camera Based on H.264 Video Coding Information
Nat. Central Univ., Taoyuan;
DOI: 10.1109/FGCN.2007.191 Conference: Future generation communication and networking (fgcn 2007), Volume: 1 Source: IEEE Xplore

Conference Paper: Motion Segmentation Algorithm for Dynamic Scenes over H.264 Video.
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ABSTRACT: In this paper, a novel algorithm to carry out the segmentation of moving objects in dynamic cameras is proposed. The developed system distinguishes what actions to execute in function of the environment conditions. In this way, the algorithm can segment objects in static and dynamic scenes and in ideal and noisy conditions. Therefore, the main target of this system is to cover the wider range of ambient situations. The segmentation algorithms have been developed for H.264 compressed domain because it is a modern encoder used in many modern multimedia applications and it can be decoded in realtime. Experimental results show promising performance in standard video sequences.Information Processing and Management of Uncertainty in KnowledgeBased Systems. Applications  13th International Conference, IPMU 2010, Dortmund, Germany, June 28  July 2, 2010. Proceedings, Part II; 01/2010  [Show abstract] [Hide abstract]
ABSTRACT: This paper presents a new method to distinguish the foreground from compressed videos. It demonstrates that the foreground detection can be effectively achieved by the local motion combine luminance and chromaticity factors. In order to calculate the local motion, which is estimated from the original motion and the global motion, we built a four –parameter model to compute global motion. LevenbergMarquardt algorithm is introduced to revise those parameters. For luminance and chromaticity factors, DC coefficients are employed to segment the objects, which are considered as the index of the image. Some implement results show that our algorithm provides a practical way for foreground extraction and more researches of high level video processing will be carried out based on it.Measuring Technology and Mechatronics Automation, International Conference on. 01/2010; 2:711714.  [Show abstract] [Hide abstract]
ABSTRACT: A new algorithm to distinguish the foreground from compressed videos is proposed in this paper. Local motion, which is estimated from the residual between the original motion and the global motion, is one of the strongest influences on visual attention. Global motion is modeled by four parameters related to camera pan, tilt, zoom and rotation. The initial parameters are obtained from the leastsquares method and updated iteratively using the LevenbergMarquardt algorithm. Temporal and spatial filters are also introduced to revise the final global motion. In addition, DC coefficients are employed to refine the result based on the local motion. Experiments show that the proposed algorithm can segment foreground effectively with a largely reduced computational complexity, as DC coefficients and motion vectors can easily be extracted from compressed videos.07/2008;
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