Comparison of view-based object recognition algorithms using realistic 3D models

  • V. Blanz
  • B. Schölkopf
  • H. Bülthoff
  • C. Burges
  • V. Vapnik
  • T. Vetter
Oral Presentations: Applications Image Processing Applications
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1112)

Abstract

Two view-based object recognition algorithms are compared: (1) a heuristic algorithm based on oriented filters, and (2) a support vector learning machine trained on low-resolution images of the objects. Classification performance is assessed using a high number of images generated by a computer graphics system under precisely controlled conditions. Training- and test-images show a set of 25 realistic three-dimensional models of chairs from viewing directions spread over the upper half of the viewing sphere. The percentage of correct identification of all 25 objects is measured.

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Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • V. Blanz
    • 1
    • 2
  • B. Schölkopf
    • 1
    • 2
  • H. Bülthoff
    • 1
  • C. Burges
    • 2
  • V. Vapnik
    • 2
  • T. Vetter
    • 1
  1. 1.Max-Planck-Institut für biologische KybernetikTübingenGermany
  2. 2.AT&T Bell LaboratoriesHolmdelUSA

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