Title :
Probabilistic relaxation for matching problems in computer vision
Author :
Kittler, J. ; Christmas, W.J. ; Petrou, M.
Author_Institution :
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
Abstract :
The authors present the theory of probabilistic relaxation for matching symbolic structures, derive as limiting cases the various heuristic formulas used by researchers in matching problems, and state the conditions under which they apply. They successfully apply the theory to the problem of matching and recognizing aerial road network images based on road network models and to the problem of edge matching in a stereo pair. For this purpose, each line network is represented by an attributed relational graph where each node is a straight line segment characterized by certain attributes and related with every other node via a set of binary relations
Keywords :
computer vision; image matching; stereo image processing; aerial road network images; attributed relational graph; attributes; binary relations; computer vision; edge matching; heuristic formulas; line network; matching problems; probabilistic relaxation; road network models; stereo pair; straight line segment; symbolic structures; Computer vision; Feature extraction; Image fusion; Image segmentation; Motion estimation; Object recognition; Polynomials; Roads; Simulated annealing; Stereo vision;
Conference_Titel :
Computer Vision, 1993. Proceedings., Fourth International Conference on
Conference_Location :
Berlin
Print_ISBN :
0-8186-3870-2
DOI :
10.1109/ICCV.1993.378148
