Combined Depth and Outlier Estimation in Multi-View Stereo
Christoph Strecha, Rik Fransens, Luc Van Gool and Luc Van Gool
In: IEEE Conference on Computer Vision and Pattern Recognition, 17-22 June 2006, New York, USA.
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 two are contaminated
by independently moving objects.
|EPrint Type:||Conference or Workshop Item (Poster)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Rik Fransens|
|Deposited On:||18 August 2006|