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Issue No.03 - March (1991 vol.13)
pp: 224-251
ABSTRACT
<p>The authors show how large efficiencies can be achieved in model-based 3-D vision by combining the notions of discrete relaxation and bipartite matching. The computational approach presented is capable of pruning large segments of search space-an indispensable step when the number of objects in the model library is large and when recognition of complex objects with a large number of surfaces is called for. Bipartite matching is used for quick wholesale rejection of inapplicable models and for the determination of compatibility of a scene surface with a potential model surface taking into account relational considerations. The time complexity function associated with those aspects of the procedure that are implemented via bipartite matching is provided. The algorithms do not take more than a couple of iterations, even for objects with more than 30 surfaces.</p>
INDEX TERMS
computer vision; 3-D object recognition; bipartite matching; discrete relaxation; pruning; search space; scene surface; time complexity function; computer vision; graph theory
CITATION
W.Y. Kim, A.C. Kak, "3-D Object Recognition Using Bipartite Matching Embedded in Discrete Relaxation", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.13, no. 3, pp. 224-251, March 1991, doi:10.1109/34.75511
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