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A Minimal Solution to Relative Pose with Unknown Focal Length and Radial Distortion

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Author

Editor

  • Michael Brown
  • Tat-Jen Cham
  • Yasuyuki Matsushita

Summary, in English

In this paper, we study the minimal problem of estimating the essential matrix between two cameras with constant but unknown focal length and radial distortion. This problem is of both theoretical and practical interest and it has not been solved previously. We have derived a fast and stable polynomial solver based on Gr{\"o}bner basis method. This solver enables simultaneous auto-calibration of focal length and radial distortion for cameras. For experiments, the numerical stability of the solver is demonstrated on synthetic data. We also evaluate on real images using either RANSAC or kernel voting. Compared with the standard minimal solver, which does not model the radial distortion, our proposed solver both finds a larger set of geometrically correct correspondences on distorted images and gives an accurate estimate of the radial distortion and focal length.

Publishing year

2015

Language

English

Pages

443-456

Publication/Series

[Host publication title missing]

Volume

9004

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Conference name

The 12th Asian Conference on Computer Vision (ACCV 2014), 2014

Conference date

2014-11-01 - 2014-11-05

Conference place

Singapore, Singapore

Status

Published

Research group

  • Mathematical Imaging Group

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISSN: 1611-3349