Imposing Semi-Local Geometric Constraints for Accurate Correspondences Selection in Structure from Motion: A Game-Theoretic Perspective |
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Authors: | Andrea Albarelli Emanuele Rodolà Andrea Torsello |
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Affiliation: | 1.Dipartimento di Scienze Ambientali, Informatica, Statistica,Università Ca’ Foscari Venezia,Venice,Italy |
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Abstract: | Most Structure from Motion pipelines are based on the iterative refinement of an initial batch of feature correspondences.
Typically this is performed by selecting a set of match candidates based on their photometric similarity; an initial estimate
of camera intrinsic and extrinsic parameters is then computed by minimizing the reprojection error. Finally, outliers in the
initial correspondences are filtered by enforcing some global geometric property such as the epipolar constraint. In the literature
many different approaches have been proposed to deal with each of these three steps, but almost invariably they separate the
first inlier selection step, which is based only on local image properties, from the enforcement of global geometric consistency.
Unfortunately, these two steps are not independent since outliers can lead to inaccurate parameter estimation or even prevent
convergence, leading to the well known sensitivity of all filtering approaches to the number of outliers, especially in the
presence of structured noise, which can arise, for example, when the images present several repeated patterns. In this paper
we introduce a novel stereo correspondence selection scheme that casts the problem into a Game-Theoretic framework in order
to guide the inlier selection towards a consistent subset of correspondences. This is done by enforcing geometric constraints
that do not depend on full knowledge of the motion parameters but rather on some semi-local property that can be estimated
from the local appearance of the image features. The practical effectiveness of the proposed approach is confirmed by an extensive
set of experiments and comparisons with state-of-the-art techniques. |
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