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Exploiting Loops in the Graph of Trifocal Tensors for Calibrating a Network of Cameras

  • Jérôme Courchay
  • Arnak Dalalyan
  • Renaud Keriven
  • Peter Sturm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6312)

Abstract

A technique for calibrating a network of perspective cameras based on their graph of trifocal tensors is presented. After estimating a set of reliable epipolar geometries, a parameterization of the graph of trifocal tensors is proposed in which each trifocal tensor is encoded by a 4-vector. The strength of this parameterization is that the homographies relating two adjacent trifocal tensors, as well as the projection matrices depend linearly on the parameters. A method for estimating these parameters in a global way benefiting from loops in the graph is developed. Experiments carried out on several real datasets demonstrate the efficiency of the proposed approach in distributing errors over the whole set of cameras.

Keywords

Fundamental Matrix Less Square Estimator Projection Matrice Bundle Adjustment Fundamental Matrice 
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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Supplementary material

978-3-642-15552-9_7_MOESM1_ESM.pdf (103 kb)
Electronic Supplementary Material (103 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jérôme Courchay
    • 1
  • Arnak Dalalyan
    • 1
  • Renaud Keriven
    • 1
  • Peter Sturm
    • 2
  1. 1.IMAGINE, LIGMUniversité Paris-Est 
  2. 2.Laboratoire Jean KuntzmannINRIA Grenoble - Rhône-Alpes 

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