Foreground detection based on motion vector from compressed video

Authors:
Zhu Leiqi;Xue Ping;Zhang Qishan
Affiliations:
Beihang University, Beijing, China;Nanyang Technological University, Singapore;Beihang University, Beijing, China
Venue:
ICAIT '08 Proceedings of the 2008 International Conference on Advanced Infocomm Technology
Year:
2008

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IEEE Transactions on Image Processing

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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 least-squares method and updated iteratively using the Levenberg-Marquardt 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.