PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Combined depth and outlier estimation in multi-view stereo
Christoph Strecha, Rik Fransens, Luc Van Gool and Luc Van Gool
In: CVPR 2006, 17-22 June 2006, New York, USA.

Abstract

In this paper, we present a generative model based approach to solve the multi-view stereo problem. The input images are considered to be generated by either one of two processes: (i) an inlier process, which generates the pixels which are visible from the reference camera and which obey the constant brightness assumption, and (ii) an outlier process which generates all other pixels. Depth and visibility are jointly modelled as a hiddenMarkov Random Field, and the spatial correlations of both are explicitly accounted for. Inference is made tractable by an EM-algorithm, which alternates between estimation of visibility and depth, and optimisation of model parameters. We describe and compare two implementations of the E-step of the algorithm, which correspond to the Mean Field and Bethe approximations of the free energy. The approach is validated by experiments on challenging real-world scenes, of which

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:3543
Deposited By:Luc Van Gool
Deposited On:11 February 2008