Title :
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
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;
Conference_Titel :
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-8186-2062-5
DOI :
10.1109/ICPR.1990.118239
