Abstract
An automatic video object segmentation is proposed. The video scene is partitioned into some homogeneous regions by an automatically cluster to form regions method. Then these regions are initially classified into three categories: moving object, candidate and background using the difference information between two successive frames. The spatio-temporal energy model is constructed to determine the candidate regions to moving object or background. Some post-processing methods are utilized to achieve the more accurate segmentation object. Experimental results show that the spatial accuracy of our proposed algorithm improves about 30–50% and temporal coherency improves about 0.05–0.70 than COST211 AM.
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© 2012 Springer Science+Business Media B.V.
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Zhang, X., Zhao, X. (2012). Motion Object Segmentation Using Regions Classification and Energy Model. In: He, X., Hua, E., Lin, Y., Liu, X. (eds) Computer, Informatics, Cybernetics and Applications. Lecture Notes in Electrical Engineering, vol 107. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1839-5_59
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DOI: https://doi.org/10.1007/978-94-007-1839-5_59
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