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Symbolic Surface Descriptors

  • Ramesh Jain
  • Thawach Sripradisvarakul
  • Nancy O’Brien
Conference paper
Part of the NATO ASI Series book series (volume 42)

Abstract

Object recognition plays a very important role in many stages of manufacturing. In this paper, we discuss our approach to recognizing objects in range images using CAD databases. The models in the databases will be used to generate recognition strategies. We present some results on symbolic surface descriptors that will play an important role in both the generation of the strategy and in the recognition of objects. Symbolic surface descriptors represent global features of an object and do not change when the object is partially occluded, while local features (such as corners or edges) may disappear entirely. We have developed a technique to segment surfaces and compute their polynomial surface descriptors. In this paper we present results of our study to determine which different types of surface descriptors (such as cylindrical, spherical, elliptical, hyperbolic, etc.) can be reliably recovered from biquadratic equation models of various surfaces.

Keywords

Object Recognition Surface Type Range Image Quadric Surface Symbolic 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 1988

Authors and Affiliations

  • Ramesh Jain
    • 1
  • Thawach Sripradisvarakul
    • 1
  • Nancy O’Brien
    • 1
  1. 1.Computer Vision Research Laboratory, Electrical Engineering and Computer ScienceThe University of MichiganAnn ArborUSA

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