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Distance Images and Intermediate-Level Vision

  • Pavel Dimitrov
  • Matthew Lawlor
  • Steven W. Zucker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6667)

Abstract

Early vision is dominated by image patches or features derived from them; high-level vision is dominated by shape representation and recognition. However there is almost no work between these two levels, which creates a problem when trying to recognize complex categories such as “airports” for which natural feature clusters are ineffective. We argue that an intermediate-level representation is necessary and that it should incorporate certain high-level notions of distance and geometric arrangement into a form derivable from images. We propose an algorithm based on a reaction-diffusion equation that meets these criteria; we prove that it reveals (global) aspects of the distance map locally; and illustrate its performance on airport and other imagery, including visual illusions.

Keywords

Scale Space Image Patch Edge Density Edge Pixel Distance Image 
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 2012

Authors and Affiliations

  • Pavel Dimitrov
    • 1
  • Matthew Lawlor
    • 1
  • Steven W. Zucker
    • 1
  1. 1.Computer Science and Applied MathematicsYale UniversityNew HavenUSA

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