ML Anthology

Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets

Atiyeh Ghoreyshi, René Vidal
ECCV 2006 pp. 127-141
doi:10.1007/978-3-540-70932-9_10 /eccv/2006/ghoreyshi2006eccv-segmenting/

Abstract

We present a new algorithm for segmenting a scene consisting of multiple moving dynamic textures. We model the spatial statistics of a dynamic texture with a set of second order Ising descriptors whose temporal evolution of is governed by an AutoRegressive eXogenous (ARX) model. Given this model, we cast the dynamic texture segmentation problem in a variational framework in which we minimize the spatial-temporal variance of the stochastic part of the model. This energy functional is shown to depend explicitly on both the appearance and dynamics of the scene. Our framework naturally handles intensity and texture based image segmentation as well as dynamics based video segmentation as particular cases. Several experiments show the applicability of our method to segmenting scenes using only dynamics, only appearance, and both dynamics and appearance.

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Cite

Text

Ghoreyshi and Vidal. "Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets." European Conference on Computer Vision, 2006. doi:10.1007/978-3-540-70932-9_10

Markdown

[Ghoreyshi and Vidal. "Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets." European Conference on Computer Vision, 2006.](https://mlanthology.org/eccv/2006/ghoreyshi2006eccv-segmenting/) doi:10.1007/978-3-540-70932-9_10

BibTeX

@inproceedings{ghoreyshi2006eccv-segmenting,
  title     = {{Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets}},
  author    = {Ghoreyshi, Atiyeh and Vidal, René},
  booktitle = {European Conference on Computer Vision},
  year      = {2006},
  pages     = {127-141},
  doi       = {10.1007/978-3-540-70932-9_10},
  url       = {https://mlanthology.org/eccv/2006/ghoreyshi2006eccv-segmenting/}
}