Title :
Unsupervised dynamic texture segmentation using local spatiotemporal descriptors
Author :
Chen, Jie ; Zhao, Guoying ; Pietikäinen, Matti
Author_Institution :
Dept. of Electr. & Inf. Eng., Univ. of Oulu, Oulu, Finland
Abstract :
Dynamic texture (DT) is an extension of texture to the temporal domain. In this paper, we address the problem of segmenting DT into disjoint regions in an unsupervised way. Each region is characterized by histograms of local binary patterns and contrast in a spatiotemporal mode. It combines the motion and appearance of DT together. Experimental results show that our method is effective in segmenting regions that differ in their dynamics.
Keywords :
image motion analysis; image segmentation; image texture; spatiotemporal phenomena; histogram characterisation; local spatiotemporal descriptor; texture motion; unsupervised dynamic texture segmentation; Application software; Computerized monitoring; Fires; Histograms; Image segmentation; Level set; Machine vision; Remote monitoring; Spatiotemporal phenomena; Yttrium;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761119