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Ecological Statistics of Contour Grouping

  • James H. Elder
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

The Gestalt laws of perceptual organization were originally conceived as qualitative principles, intrinsic to the brain. In this paper, we develop quantitative models for these laws based upon the statistics of natural images. In particular, we study the laws of proximity, good continuation and similarity as they relate to the perceptual organization of contours. We measure the statistical power of each, and show how their approximate independence leads to a Bayesian factorial model for contour inference. We showho wthese local cues can be combined with global cues such as closure, simplicity and completeness, and with prior object knowledge, for the inference of global contours from natural images. Our model is generative, allowing contours to be synthesized for visualization and psychophysics.

Keywords

Natural Image Global Constraint Perceptual Organization Good Continuation Likelihood Distribution 
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 2002

Authors and Affiliations

  • James H. Elder
    • 1
  1. 1.Centre for Vision ResearchYork UniversityTorontoCanada

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