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Robust Optimal Pose Estimation

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Author

  • Olof Enqvist
  • Fredrik Kahl

Summary, in English

We study the problem of estimating the position and orientation of a calibrated camera from an image of a known scene. A common problem in camera pose estimation is the existence of false correspondences between image features and modeled 3D points. Existing techniques Such as RANSAC to handle outliers have no guarantee of optimality. In contrast, we work with a natural extension of the L-infinity norm to the outlier case. Using a simple result from classical geometry, we derive necessary conditions for L-infinity optimality and show how to use them in a branch and bound setting to find the optimum and to detect outliers. The algorithm has been evaluated on synthetic as well as real data showing good empirical performance. In addition, for cases with no outliers, we demonstrate shorter execution times than existing optimal algorithms.

Publishing year

2008

Language

English

Pages

141-153

Publication/Series

Computer Vision – ECCV 2008 (Lecture Notes in Computer Science)

Volume

5302

Document type

Conference paper

Publisher

Springer

Topic

  • Mathematics

Conference name

10th European Conference on Computer Vision (ECCV 2008)

Conference date

2008-10-12 - 2008-10-18

Conference place

Marseille, France

Status

Published

ISBN/ISSN/Other

  • ISSN: 1611-3349
  • ISSN: 0302-9743
  • ISBN: 978-3-540-88681-5