Abstract

This paper describes a graph-spectral method for path estimation. Our aim is to find a maximum probability path through a lattice of pixel sites. We characterise the path recovery problem using a site transition matrix. A graph-spectral analysis of the transition matrix reveals how the maximum probability path can be located using an eigenvector of the associated normalised affinity matrix. We demonstrate the utility of the resulting method on the problem of recovering surface height from a field of surface normals.

Keywords

Markov Chain Sectional Curvature Surface Normal Integration Path Transition Probability Matrix 
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

  • Antonio Robles-Kelly
    • 1
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK

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