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Spatially Homogeneous Dynamic Textures

  • Gianfranco Doretto
  • Eagle Jones
  • Stefano Soatto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3022)

Abstract

We address the problem of modeling the spatial and temporal second-order statistics of video sequences that exhibit both spatial and temporal regularity, intended in a statistical sense. We model such sequences as dynamic multiscale autoregressive models, and introduce an efficient algorithm to learn the model parameters. We then show how the model can be used to synthesize novel sequences that extend the original ones in both space and time, and illustrate the power, and limitations, of the models we propose with a number of real image sequences.

Keywords

Video Sequence Singular Value Decomposition Texture Synthesis Dynamic Texture Temporal Regularity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Gianfranco Doretto
    • 1
  • Eagle Jones
    • 1
  • Stefano Soatto
    • 1
  1. 1.UCLA Computer Science DepartmentLos AngelesUSA

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