Dense stereo by triangular meshing and cross validation

Authors:
Peter Wey;Bernd Fischer;Herbert Bay;Joachim M. Buhmann
Affiliations:
Institute of Computational Science;Institute of Computational Science;Computer Vision Laboratory, ETH Zurich, Switzerland;Institute of Computational Science
Venue:
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Year:
2006

Citing 6
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Abstract

Dense depth maps can be estimated in a Bayesian sense from multiple calibrated still images of a rigid scene relative to a reference view [1]. This well-established probabilistic framework is extended by adaptively refining a triangular meshing procedure and by automatic cross-validation of model parameters. The adaptive refinement strategy locally adjusts the triangular meshing according to the measured image data. The new method substantially outperforms the competing techniques both in terms of robustness and accuracy.