Multiresolution stereo-a Bayesian approach

Author

Chang, Chienchung ; Chatterjee, Shankar

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA

Volume

i

fYear

1990

fDate

16-21 Jun 1990

Firstpage

908

Abstract

A Bayesian approach is proposed for stereo matching to derive the maximum a posteriori estimation of depth. How a pyramid data structure can be combined with simulated annealing to speed up convergence in stereo matching is described. Using the invariant property of image intensity and modeling the disparity as a Markov random field (MRF), the pyramid structure is followed from high (coarse) level to low (fine) level to derive the maximum a posteriori estimates. Simulation results on both random dot diagrams and synthesized images show the promise of this multiresolution stereo approach

Keywords

Bayes methods; Markov processes; data structures; pattern recognition; picture processing; simulated annealing; Bayesian approach; Markov random field; convergence; depth estimation; image intensity; multiresolution stereo matching; pattern recognition; picture processing; pyramid data structure; simulated annealing; Bayesian methods; Convergence; Data structures; Laboratories; Markov random fields; Optical computing; Signal analysis; Signal resolution; Simulated annealing; Spatial resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1990. Proceedings., 10th International Conference on

Conference_Location

Atlantic City, NJ

Print_ISBN

0-8186-2062-5

Type

conf

DOI

10.1109/ICPR.1990.118239

Filename

118239