17 March 2017 Variational frame difference models for motion segmentation
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Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034115 (2017) https://doi.org/10.1117/12.2268504
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
Abstract
Frame difference method is a good method for motion segmentation, but its result contains much wrong motion regions and incomplete motion objects. In this paper we combine variational method with frame difference method to propose two motion segmentation models, and the proposed models are based on different invariance assumptions. The models can detect motion objects and make up for the inadequacy of frame differential method with smooth terms. Experimental results show that the proposed models can detect motion objects better.
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Bowen Liu, Weibo Wei, Zhenkuan Pan, Shourun Wang, "Variational frame difference models for motion segmentation", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034115 (17 March 2017); doi: 10.1117/12.2268504; https://doi.org/10.1117/12.2268504
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