DocumentCode :
3056123
Title :
Multiscale stereo matching
Author :
Lew, Michael S. ; Wong, Kam W. ; Huang, Thomas S.
Author_Institution :
Illinois Univ., Urbana, IL, USA
fYear :
1992
fDate :
30 Aug-3 Sep 1992
Firstpage :
620
Lastpage :
623
Abstract :
Most work in pyramidal or hierarchical stereo matching has primarily used the direct coarse-to-fine or hill climbing search method. However, there are two significant problems in using the hill climbing method. First, the match at the initial scale level can be wrong. Second, the binary decision at any of the finer scale levels may be wrong. The authors present a method which is essentially a best-first or cost minimization search method and which alleviates both of these problems. Results of application to real world image pairs are presented as well as a direct comparison in terms of percentage of correct matches to the traditional hill climbing method
Keywords :
image processing; minimisation; pattern recognition; search problems; best-first search method; cost minimization search method; direct coarse-to-fine method; hierarchical stereo matching; hill climbing search method; multiscale stereo matching; pyramidal stereo matching; Binary trees; Brightness; Costs; Error correction; Image matching; Minimization methods; Roads; Search methods; Switches; Terrain mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1992. Vol.I. Conference A: Computer Vision and Applications, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2910-X
Type :
conf
DOI :
10.1109/ICPR.1992.201638
Filename :
201638
Link To Document :
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