Abstract
In this paper, a novel scheme for fast object segmentation and tracking in MPEG-2 compressed domain is proposed. The video object is finally extracted after steps of motion detection, vector-based watershed segmentation, fusing operation, and finally edge correcting and morphologic post-processing. The tracking algorithm is fast and simple. All the processes are mainly implemented in compressed domain without the need of fully decoding of compressed stream. The information of motion vectors and DCT coefficients used in the algorithm are directly extracted from the compressed stream. Experimental results reveal that the proposed algorithm can extract objects directly from compressed stream with accurate contours and the object tracking algorithm is also efficient.
This work was partially supported by the Natural Science Foundation of Ningbo, China (200601A6301025); the Open Project Foundation of National Key Laboratory of Machine Perception of Peking University (2005176); the Foundation of Education Ministry of Zhejiang Province, China (200502123); Key Scientific and Technological Project of Ningbo, China (2005B100003).
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Zhu, ZJ., Wang, YE., Zhang, ZN., Jiang, GY. (2006). Novel Scheme for Automatic Video Object Segmentation and Tracking in MPEG-2 Compressed Domain. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing in Signal Processing and Pattern Recognition. Lecture Notes in Control and Information Sciences, vol 345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37258-5_125
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DOI: https://doi.org/10.1007/978-3-540-37258-5_125
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