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A finite mixture model for detail-preserving image segmentation.

, , , and . Signal Process., 93 (11): 3171-3181 (2013)

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Multiresolution Based Gaussian Mixture Model for Background Suppression., , and . IEEE Trans. Image Process., 22 (12): 5022-5035 (2013)Enhancing the Potential of the Conventional Gaussian Mixture Model for Segmentation: from Images to Videos.. University of Windsor, Ontario, Canada, (2014)base-search.net (ftunivwindsor:oai:scholar.uwindsor.ca:etd-6259).An Online Unsupervised Feature Selection and its Application for Background Suppression., , and . CRV, page 161-168. IEEE Computer Society, (2015)Streaming spatio-temporal video segmentation using Gaussian Mixture Model., and . ICIP, page 4388-4392. IEEE, (2014)Motion Segmentation Based on 3D Histogram and Temporal Mode Selection., and . ICME Workshops, page 483-488. IEEE Computer Society, (2012)A finite mixture model for detail-preserving image segmentation., , , and . Signal Process., 93 (11): 3171-3181 (2013)A Fast Two Pass Multi-Value Segmentation Algorithm based on Connected Component Analysis.. CoRR, (2014)A comparative experimental study of image feature detectors and descriptors., , and . Mach. Vis. Appl., 26 (4): 443-466 (2015)Real-timeVideoSegmentation Using Student'stMixture Model., and . ANT/MobiWIS, volume 10 of Procedia Computer Science, page 153-160. Elsevier, (2012)Feature Ranking in Dynamic Texture Clustering., , and . CRV, page 109-116. IEEE Computer Society, (2015)