Camera Resectioning from a Box

  • Henrik Aanæs
  • Klas Josephson
  • François Anton
  • Jakob Andreas Bærentzen
  • Fredrik Kahl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5575)


In this paper we describe how we can do camera resectioning from a box with unknown dimensions, i.e. determine the camera model, assuming that image pixels are square. This assumption is equivalent to assuming that the camera has an aspect ratio of one and zero skew, and this holds for most — if not all — digital cameras. Our proposed method works by first deriving 9 linear constraints on the projective camera matrix from the box, leaving a 3-dimensional subspace in which the projective camera matrix can lie. A single solution in this 3D subspace is then found via a method by Triggs in 1999, which uses the square pixel assumption to set up a 4th degree polynomial to which the solution is the desired model. This approach is, however, numerically challenging, and we use several means to tackle this issue. Lastly the solution is refined in an iterative manner, i.e. using bundle adjustment.


Polynomial Equation Null Space Cholesky Factorization Bundle Adjustment Calibration Matrix 
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 2009

Authors and Affiliations

  • Henrik Aanæs
    • 1
  • Klas Josephson
    • 2
  • François Anton
    • 1
  • Jakob Andreas Bærentzen
    • 1
  • Fredrik Kahl
    • 2
  1. 1.DTU InformaticsTechnical University of DenmarkLyngbyDenmark
  2. 2.Centre For Mathematical SciencesLund UniversityLundSweden

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