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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Fast Dynamic Texture Detection
verfasst von : V. Javier Traver, Majid Mirmehdi, Xianghua Xie, Raúl Montoliu
Erschienen in: Computer Vision – ECCV 2010
Verlag: Springer Berlin Heidelberg
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Dynamic textures can be considered to be spatio-temporally varying visual patterns in image sequences with certain temporal regularity. We propose a novel and efficient approach to explore the violation of the brightness constancy assumption, as an indication of presence of dynamic texture, using simple optical flow techniques. We assume that dynamic texture regions are those that have poor spatio-temporal optical flow coherence. Further, we propose a second approach that uses robust global parametric motion estimators that effectively and efficiently detect motion outliers, and which we exploit as powerful cues to localize dynamic textures. Experimental and comparative studies on a range of synthetic and real-world dynamic texture sequences show the feasibility of the proposed approaches, with results which are competitive to or better than recent state-of-art approaches and significantly faster.