Object-based video segmentation is an important issue for many multimedia applications. A video segmentation method based on EM algorithm is proposed. We consider video segmentation as an unsupervised classification problem and apply EM algorithm to obtain the maximum-likelihood estimation of the Gaussian model parameters for model-based segmentation. We simultaneously combine multiple features (motion, color) within a maximum likelihood framework to obtain accurate segment results. We also use the temporal consistency among video frames to improve the speed of EM algorithm. Experimental results on typical MPEG-4 sequences and real scene sequences show that our method has an attractive accuracy and robustness.
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