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On Computing Metric Upgrades of Projective Reconstructions under the Rectangular Pixel Assumption

  • Jean Ponce
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2018)

Abstract

This paper shows how to upgrade the projective reconstruction of a scene to a metric one in the case where the only assumption made about the cameras observing that scene is that they have rectangular pixels (zero-skew cameras). The proposed approach is based on a simple characterization of zero-skew projection matrices in terms of line geometry, and it handles zero-skew cameras with arbitrary or known aspect ratios in a unified framework. The metric upgrade computation is decomposed into a sequence of linear operations, including linear least-squares parameter estimation and eigenvalue-based symmetric matrix factorization, followed by an optional non-linear least-squares refinement step. A few classes of critical motions for which a unique solution cannot be found are spelled out. A MATLAB implementation has been constructed and preliminary experiments with real data are presented.

Keywords

Projective Transformation Optical Center Quadratic Constraint Projection Matrice World Coordinate System 
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 2001

Authors and Affiliations

  • Jean Ponce
    • 1
  1. 1.Dept. of Computer Science and Beckman InstituteUniversity of Illinois at Urbana-ChampaignUSA

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