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Simultaneous Multiple Rotation Averaging using Lagrangian Duality

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Author

Summary, in English

Multiple rotation averaging is an important problem in computer vision. The problem is challenging because of the nonlinear constraints required to represent the set of rotations. To our knowledge no one has proposed any globally optimal solution for the case of simultaneous updates of the rotations. In this paper we propose a simple procedure based on Lagrangian duality that can be used to verify global optimality of a local solution, by solving a linear system of equations. We show experimentally on real and synthetic data that unless the noise levels are extremely high this procedure always generates the globally optimal solution.

Publishing year

2013

Language

English

Pages

245-258

Publication/Series

Lecture Notes in Computer Science (Computer Vision - ECCV 2012, 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5-9, 2012, Revised Selected Papers, Part III)

Volume

7726

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Keywords

  • computer vision
  • rotation averaging
  • optimization
  • duality

Conference name

11th Asian Conference on Computer Vision (ACCV 2012), 2012

Conference date

2012-11-05 - 2012-11-09

Status

Published

Research group

  • Mathematical Imaging Group

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISSN: 1611-3349
  • ISBN: 978-3-642-37430-2 (print)
  • ISBN: 978-3-642-37431-9 (online)