Multiple temporal texture detection using feature space mapping
Proceedings of the 6th ACM international conference on Image and video retrieval
A Comparison of Wavelet Based Spatio-temporal Decomposition Methods for Dynamic Texture Recognition
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Detection of multiple dynamic textures using feature space mapping
IEEE Transactions on Circuits and Systems for Video Technology
DynTex: A comprehensive database of dynamic textures
Pattern Recognition Letters
Change detection for temporal texture in the Fourier domain
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Segmenting dynamic textures with ising descriptors, ARX models and level sets
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Visual crowd surveillance through a hydrodynamics lens
Communications of the ACM
Texture databases - A comprehensive survey
Pattern Recognition Letters
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A dynamic texture is a linear dynamical system used to model a single video as a sample from a spatio-temporal stochastic process. In this work, we introduce the mixture of dynamic textures, which models a collection of videos consisting of different visual processes as samples from a set of dynamic textures. We derive the EM algorithm for learning a mixture of dynamic textures, and relate the learning algorithm and the dynamic texture mixture model to previous works. Finally, we demonstrate the applicability of the proposed model to problems that have traditionally been challenging for computer vision.