Surface based hypothesis verification in intensity images using geometric and appearance data

  • J. H. M. Byne
  • J. A. D. W. Anderson
Poster Session II

DOI: 10.1007/3-540-63931-4_213

Volume 1352 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Byne J.H.M., Anderson J.A.D.W. (1997) Surface based hypothesis verification in intensity images using geometric and appearance data. In: Chin R., Pong TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg

Abstract

In this paper we discuss current work concerning Appearance-based and CAD-based vision; two opposing vision strategies. CAD-based vision is geometry based, reliant on having complete object centred models. Appearance-based vision builds view dependent models from training images. Existing CAD-based vision systems that work with intensity images have all used one and zero dimensional features, for example lines, arcs, points and corners. We describe a system we have developed for combining these two strategies. Geometric models are extracted from a commercial CAD library of industry standard parts. Surface appearance characteristics are then learnt automatically by observing actual object instances. This information is combined with geometric information and is used in hypothesis evaluation. This augmented description improves the systems robustness to texture, specularities and other artifacts which are hard to model with geometry alone, whilst maintaining the advantages of a geometric description.

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Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • J. H. M. Byne
    • 1
  • J. A. D. W. Anderson
    • 1
  1. 1.Dept. of Computer ScienceUniversity of ReadingBerksUK