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Bayesian Stereo Matching

Cheng , Li; Caelli, Terry


A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given the observed stereo images. A mixed sampling and deterministic strategy is adopted to balance between effectiveness and efficiency: the parameters are estimated via Markov Chain Monte Carlo sampling techniques and the Maximum A Posteriori (MAP) disparity map is inferred by a deterministic approximation algorithm....[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Journal article
Source: Computer Vision and Image Understanding
DOI: 10.1016/j.cviu.2005.09.009


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