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Maximizing Rigidity: Optimal Matching under Scaled-Orthography

  • João Maciel
  • João Costeira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)

Abstract

Establishing point correspondences between images is a key step for 3D-shape computation. Nevertheless, shape extraction and point correspondence are treated, usually, as two different computational processes. We propose a new method for solving the correspondence problem between points of a fully uncalibrated scaled-orthographic image sequence. Among all possible point selections and permutations, our method chooses the one that minimizes the fourth singular value of the observation matrix in the factorization method. This way, correspondences are set such that shape and motion computation are optimal. Furthermore, we show this is an optimal criterion under bounded noise conditions.

Also, our formulation takes feature selection and outlier rejection into account, in a compact and integrated way. The resulting combinatorial problem is cast as a concave minimization problem that can be efficiently solved. Experiments show the practical validity of the assumptions and the overall performance of the method.

Keywords

Optimal Match Point Correspondence Correspondence Problem Outlier Rejection Epipolar Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • João Maciel
    • 1
  • João Costeira
    • 1
  1. 1.Instituto de Sistemas e Robotica, Instituto Superior TecnicoPortugal

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