Dynamic Textures: Modeling the Temporal Statistics

3 minute read

In nature there are plenty of scenes that originate video sequences showing temporal “repetition,” intended in a statistical sense. One could think of a flow of water, a fire, or a flow of car traffic or people walking. This kind of visual processes are now referred to as dynamic textures. (Doretto et al., 2003; Soatto et al., 2001) propose to study dynamic textures as stochastic processes that exhibit temporal stationarity, and introduce the use of linear dynamic systems for modeling their second-order statistical properties. They derived procedures for learning and simulating a dynamic texture model, and demonstrated its effectiveness in several cases using prediction error methods. The formalization is technically sound, and the model has been used in the literature to tackle many other problems by several other authors.


  1. IJCV
    Dynamic textures Doretto, G., Chiuso, A., Wu, Y. N., and Soatto, S. International Journal of Computer Vision, 2003. abstract bibTeX pdf
  2. ICCV
    Dynamic textures Soatto, S., Doretto, G., and Wu, Y. N. In Proceedings of IEEE International Conference on Computer Vision, 2001. Oral abstract bibTeX pdf