Structural Stereopsis for 3-D Vision

  • Authors:
  • K. L. Boyer;A. C. Kak

  • Affiliations:
  • Ohio State Univ., Columbus;Purdue Univ., West Lafayette, IN

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 1988

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Abstract

A novel approach to solving the stereo correspondence problem in computer vision is described. Structural descriptions of two two-dimensional views of a scene are extracted by one of possibly several available low-level processes, and a new theory of inexact matching for such structures is derived. An entropy-based figure of merit for attribute selection and ordering is defined. Experimental results applying these techniques to real image pairs are presented. Some manipulation experiments are briefly presented.