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Issue No.02 - March (1988 vol.10)
pp: 144-166
<p>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.</p>
3D comput vision; computerised pattern recognition; robot vision; structural stereopsis; 2D views; stereo correspondence; inexact matching; entropy-based figure of merit; image pairs; computer vision; computerised pattern recognition; statistical analysis
K.L. Boyer, A.C. Kak, "Structural Stereopsis for 3-D Vision", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.10, no. 2, pp. 144-166, March 1988, doi:10.1109/34.3880
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