Phase based modelling of dynamic textures

Bernard Ghanem, Narendra Ahuja

Research output: Contribution to conferencePaper

Abstract

This paper presents a model of spatiotemporal variations in a dynamic texture (DT) sequence. Most recent work on DT modelling represents images in a DT sequence as the responses of a linear dynamical system (LDS) to noise. Despite its merits, this model has limitations because it attempts to model temporal variations in pixel intensities which do not take advantage of global motion coherence. We propose a model that relates texture dynamics to the variation of the Fourier phase, which captures the relationships among the motions of all pixels (i.e. global motion) within the texture, as well as the appearance of the texture. Unlike LDS, our model does not require segmentation or cropping during the training stage, which allows it to handle DT sequences containing a static background. We test the performance of this model on recognition and synthesis of DT's. Experiments with a dataset that we have compiled demonstrate that our phase based model outperforms LDS.

Original languageEnglish (US)
DOIs
StatePublished - Dec 1 2007
Event2007 IEEE 11th International Conference on Computer Vision, ICCV - Rio de Janeiro, Brazil
Duration: Oct 14 2007Oct 21 2007

Other

Other2007 IEEE 11th International Conference on Computer Vision, ICCV
CountryBrazil
CityRio de Janeiro
Period10/14/0710/21/07

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ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Ghanem, B., & Ahuja, N. (2007). Phase based modelling of dynamic textures. Paper presented at 2007 IEEE 11th International Conference on Computer Vision, ICCV, Rio de Janeiro, Brazil. https://doi.org/10.1109/ICCV.2007.4409094