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Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2
Dynamic Texture Segmentation
Nice, France
October 13-October 16
ISBN: 0-7695-1950-4
Paolo Favaro, UCLA; Washington University, St. Louis
We address the problem of segmenting a sequence of images of natural scenes into disjoint regions that are characterized by constant spatio-temporal statistics. We model the spatio-temporal dynamics in each region by Gauss-Markov models, and infer the model parameters as well as the boundary of the regions in a variational optimization framework. Numerical results demonstrate that - in contrast to purely texture-based segmentation schemes - our method is effective in segmenting regions that differ in their dynamics even when spatial statistics are identical.
Citation:
Gianfranco Doretto, Daniel Cremers, Paolo Favaro, Stefano Soatto, "Dynamic Texture Segmentation," iccv, vol. 2, pp.1236, Ninth IEEE International Conference on Computer Vision (ICCV'03) - Volume 2, 2003
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