A brute-force algorithm for reconstructing a scene from two projections

Is the real problem in finding the relative orientation of two viewpoints the correspondence problem? We argue that this is only one difficulty. Even with known correspondences, popular methods like the eight point algorithm and minimal solvers may break down due to planar scenes or small relative m...

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Vydáno v:CVPR 2011 s. 2961 - 2968
Hlavní autoři: Enqvist, O., Fangyuan Jiang, Kahl, F.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.01.2011
Témata:
Approximation methods
Computer vision
Cost function
Motion segmentation
Three dimensional displays
Tracking
Upper bound
ISBN:1457703947, 9781457703942
ISSN:1063-6919, 1063-6919
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Abstract Is the real problem in finding the relative orientation of two viewpoints the correspondence problem? We argue that this is only one difficulty. Even with known correspondences, popular methods like the eight point algorithm and minimal solvers may break down due to planar scenes or small relative motions. In this paper, we derive a simple, brute-force algorithm which is both robust to outliers and has no such algorithmic degeneracies. Several cost functions are explored including maximizing the consensus set and robust norms like truncated least-squares. Our method is based on parameter search in a four-dimensional space using a new epipolar parametrization. In principle, we do an exhaustive search of parameter space, but the computations are very simple and easily parallelizable, resulting in an efficient method. Further speed-ups can be obtained by restricting the domain of possible motions to, for example, planar motions or small rotations. Experimental results are given for a variety of scenarios including scenes with a large portion of outliers. Further, we apply our algorithm to 3D motion segmentation where we outperform state-of-the-art on the well-known Hopkins-155 benchmark database.
AbstractList Is the real problem in finding the relative orientation of two viewpoints the correspondence problem? We argue that this is only one difficulty. Even with known correspondences, popular methods like the eight point algorithm and minimal solvers may break down due to planar scenes or small relative motions. In this paper, we derive a simple, brute-force algorithm which is both robust to outliers and has no such algorithmic degeneracies. Several cost functions are explored including maximizing the consensus set and robust norms like truncated least-squares. Our method is based on parameter search in a four-dimensional space using a new epipolar parametrization. In principle, we do an exhaustive search of parameter space, but the computations are very simple and easily parallelizable, resulting in an efficient method. Further speed-ups can be obtained by restricting the domain of possible motions to, for example, planar motions or small rotations. Experimental results are given for a variety of scenarios including scenes with a large portion of outliers. Further, we apply our algorithm to 3D motion segmentation where we outperform state-of-the-art on the well-known Hopkins-155 benchmark database.
Author Kahl, F.
Enqvist, O.
Fangyuan Jiang
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  surname: Kahl
  fullname: Kahl, F.
  email: fredrik@maths.ith.se
  organization: Centre for Math. Sci., Lund Univ., Lund, Sweden
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Snippet Is the real problem in finding the relative orientation of two viewpoints the correspondence problem? We argue that this is only one difficulty. Even with...
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StartPage 2961
SubjectTerms Approximation methods
Computer vision
Cost function
Motion segmentation
Three dimensional displays
Tracking
Upper bound
Title A brute-force algorithm for reconstructing a scene from two projections
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