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Combining Appearance and Topology for Wide Baseline Matching

  • Dennis Tell
  • Stefan Carlsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2350)

Abstract

The problem of establishing image-to-image correspondences is fundamental in computer vision. Recently, several wide baseline matching algorithms capable of handling large changes of viewpoint have appeared. By computing feature values from image data, these algorithms mainly use appearance as a cue for matching. Topological information, i.e. spatial relations between features, has also been used, but not nearly to the same extent as appearance. In this paper, we incorporate topological constraints into an existing matching algorithm [1] which matches image intensity profiles between interest points. We show that the algorithm can be improved by exploiting the constraint that the intensity profiles around each interest point should be cyclically ordered. String matching techniques allows for an efficient implementation of the ordering constraint. Experiments with real data indicate that the modified algorithm indeed gives superior results to the original one. The method of enforcing the spatial constraints is not limited to the presented case, but can be used on any algorithm where interest point correspondences are sought.

Keywords

Interest Point String Match Left Image Cyclic Order Longe Common Subsequence 
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

  • Dennis Tell
    • 1
  • Stefan Carlsson
    • 1
  1. 1.Dept. of Numerical Analysis and Computer Science KTHComputational Vision and Active Perception Laboratory (CVAP)StockholmSweden

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