| M. Pelillo, K. Siddiqi, and S. W. Zucker, "Continuous-based heuristics for graph and tree isomorphisms, with application to computer vision," in NIPS 99 Workshop on Complexity and Neural Computation, Dec. 1999. |
....deeper analysis is achieved via hash coding, that is, splitting graphs to elements and comparing the obtained structures. Heuristic techniques can be used also in matching; methods applying randomized computation (simulated annealing, 9] and continuous space optimization (quadratic programming, [5]) have been proposed. In this paper we present a new heuristic matching scheme for attribute trees. The proposed scheme, consisting of preparatory index calculation and actual matching, can be carried out in time linearly proportional to the number of nodes of the source trees. In general, ....
M. Pelillo, K. Siddiqi, and S. W. Zucker. Continuous-based heuristics for graph and tree isomorphisms, with application to computer vision. In P. M. Pardalos, editor, Approximation and Complexity in Numerical Optimization: Continuous and Discrete Problems. Kluwer Academic Publishers, Boston, MA, 1999. In press.
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M. Pelillo, K. Siddiqi, and S. W. Zucker, "Continuous-based heuristics for graph and tree isomorphisms, with application to computer vision," in NIPS 99 Workshop on Complexity and Neural Computation, Dec. 1999.
No context found.
M. Pelillo, K. Siddiqi, and S. W. Zucker, "Continuous-based heuristics for graph and tree isomorphisms, with application to computer vision," in NIPS 99 Workshop on Complexity and Neural Computation, Dec. 1999. # The video images shown in this paper have copyright by ZDF (Zweites Deutsches Fernsehen), Germany. (a) input image (b) found object model (second from the right)
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