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Spiders as Robust Point Descriptors

  • Adam Stanski
  • Olaf Hellwich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3663)

Abstract

This paper introduces a new operator to characterize a point in an image in a distinctive and invariant way. The robust recognition of points is a key technique in computer vision: algorithms for stereo correspondence, motion tracking and object recognition rely heavily on this type of operator. The goal in this paper is to describe the salient point to be characterized by a constellation of surrounding anchor points. Salient points are the most reliably localized points extracted by an interest point operator. The anchor points are multiple interest points in a visually homogenous segment surrounding the salient point. Because of its appearance, this constellation is called a spider. With a prototype of the spider operator, results in this paper demonstrate how a point can be recognized in spite of significant image noise, inhomogeneous change in illumination and altered perspective. For an example that requires a high performance close to object / background boundaries, the prototype yields better results than David Lowe’s SIFT operator.

Keywords

Object Recognition Anchor Point Interest Point Salient Point Sift Descriptor 
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 2005

Authors and Affiliations

  • Adam Stanski
    • 1
  • Olaf Hellwich
    • 1
  1. 1.Computer Vision & Remote Sensing GroupTechnical University of BerlinBerlinGermany

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