Simultaneous Multiple Rotation Averaging using Lagrangian Duality

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.

• Författare: Johan Fredriksson; Carl Olsson
• Avdelning/ar: Matematik LTH; Mathematical Imaging Group; ELLIIT: the Linköping-Lund initiative on IT and mobile communication; eSSENCE: The e-Science Collaboration
• Publiceringsår: 2013
• Språk: Engelska
• Sidor: 245-258
• Publikation/Tidskrift/Serie: 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)
• Volym: 7726
• Länkar: http://link.springer.com/chapter/10.1007/978-3-642-37431-9_19
• Dokumenttyp: Konferensbidrag
• Förlag: Springer
• Ämne: Computer Vision and Robotics (Autonomous Systems); Mathematics
• Nyckelord: 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
• Forskningsgrupp: Mathematical Imaging Group
• ISBN/ISSN/Övrigt: ISSN: 0302-9743; ISSN: 1611-3349; ISBN: 978-3-642-37430-2 (print); ISBN: 978-3-642-37431-9 (online)