Title :
Concurrent propagation for solving ill-posed problems of global discrete optimisation
Author :
Gimel´farb, G. ; Rui Gong ; Nicolescu, Radu ; Delmas, Patrice
Author_Institution :
Dept. of Comput. Sci., Univ. of Auckland, Auckland, New Zealand
Abstract :
Classical frameworks for global 1D discrete optimisation: dynamic programming (DP) and belief propagation (BP) - presume well-posed problems with unique solutions. Ill-posed problems, being the most common in applied pattern recognition and computer vision, are regularised to restore well-posedness. However, typical heuristic regularisation does not guarantee that a set of multiple equivalent solutions is reduced to a single solution. An alternative concurrent propagation (CP) proposed in this paper extends the DP to allow for determining whether the problem is well- or ill-posed and storing implicitly in the latter case the entire set of solutions (e.g. for its structural analysis to improve regularisation). The CP, DP, and BP have similar computational complexity.
Keywords :
belief networks; computational complexity; computer vision; concurrency theory; dynamic programming; problem solving; 1D global discrete optimisation; BP; CP; DP; belief propagation; computational complexity; computer vision; concurrent propagation; dynamic programming; ill posed problem solving; pattern recognition; structural analysis; Computer vision; Dynamic programming; Image color analysis; Linear programming; Optimization; Pattern recognition; Stereo image processing;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4