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How to Overcome Perceptual Aliasing in ASIFT?

  • Nicolas Noury
  • Frédéric Sur
  • Marie-Odile Berger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6453)

Abstract

SIFT is one of the most popular algorithms to extract points of interest from images. It is a scale+rotation invariant method. As a consequence, if one compares points of interest between two images subject to a large viewpoint change, then only a few, if any, common points will be retrieved. This may lead subsequent algorithms to failure, especially when considering structure and motion or object recognition problems. Reaching at least affine invariance is crucial for reliable point correspondences. Successful approaches have been recently proposed by several authors to strengthen scale+rotation invariance into affine invariance, using viewpoint simulation (e.g. the ASIFT algorithm). However, almost all resulting algorithms fail in presence of repeated patterns, which are common in man-made environments, because of the so-called perceptual aliasing. Focusing on ASIFT, we show how to overcome the perceptual aliasing problem. To the best of our knowledge, the resulting algorithm performs better than any existing generic point matching procedure.

Keywords

Simulated Image Repeated Pattern Sift Feature Epipolar Line Epipolar Geometry 
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 2010

Authors and Affiliations

  • Nicolas Noury
    • 1
  • Frédéric Sur
    • 1
  • Marie-Odile Berger
    • 1
  1. 1.Magrit Project-TeamUHP / INPL / INRIANancyFrance

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