Abstract
A new automatic video sequence segmentation algorithm that extracts moving objects is presented in this paper. The algorithm exploits the local variation in the L*u*v* space, and combines it with motion information to separate foreground objects from the background. A new image segmentation algorithm based on graphic-theoretic approach is first employed to generate various regions according to local variation. Next, moving regions are identified by a new filter criterion, which measures the deviation of the estimated local motion from the synthesized global motion. In order to increase the temporal and spatial consistency of extracted objects, moving regions are tracked by a region-based affine motion model. Two-dimensional binary models are derived for the objects and tracked throughout the sequence by a Hausdorff object tracker. The proposed algorithm is evaluated for several typical MPEG-4 test sequences. Experimental results demonstrate the performance of the proposed algorithm.
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Liu, MG., Hou, CH. (2001). Automatic Segmentation and Tracking of Moving Objects. In: Shum, HY., Liao, M., Chang, SF. (eds) Advances in Multimedia Information Processing — PCM 2001. PCM 2001. Lecture Notes in Computer Science, vol 2195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45453-5_28
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DOI: https://doi.org/10.1007/3-540-45453-5_28
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