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On Computing Visual Flows with Boundaries: The Case of Shading and Edges

  • Ohad Ben-Shahar
  • Patrick S. Huggins
  • Steven W. Zucker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

Many visual tasks depend upon the interpretation of visual structures that are flow fields, such as optical flow, oriented texture, and shading. The computation of these visual flows involves a delicate tradeo off: imaging imperfections lead to noisy and sparse initial flow measurements, necessitating further processing to infer dense coherent flows; this processing typically entails interpolation and smoothing, both of which are prone to destroy visual flow discontinuities. However, discontinuities in visual flows signal corresponding discontinuities in the physical world, thus it is critical to preserve them while processing the flow. In this paper we present a computational approach motivated by the architecture of primary visual cortex that directly incorporates boundary information into a flow relaxation network. The result is a robust computation of visual flows with the capacity to handle noisy or sparse data sets while providing stability along flow boundaries. We demonstrate the effectiveness of our approach by computing shading flows in images with intensity edges.

Keywords

Primary Visual Cortex Computing Visual Line Discontinuity Gradient Ascent Visual Flow 
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

  • Ohad Ben-Shahar
    • 1
  • Patrick S. Huggins
    • 1
  • Steven W. Zucker
    • 1
  1. 1.Department of Computer Science and Interdisciplinary Neuroscience ProgramYale UniversityNew HavenUSA

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