Global Optimization through Rotation Space Search
Författare
Summary, in English
This paper introduces a new algorithmic technique for solving certain problems in geometric computer vision. The main novelty of the method is a branch-and-bound search over rotation space, which is used in this paper to determine camera orientation. By searching over all possible rotations, problems can be reduced to known fixed-rotation problems for which optimal solutions have been previously given. In particular, a method is developed for the estimation of the essential matrix, giving the first guaranteed optimal algorithm for estimating the relative pose using a cost function based on reprojection errors. Recently convex optimization techniques have been shown to provide optimal solutions to many of the common problems in structure from motion. However, they do not apply to problems involving rotations. The search method described in this paper allows such problems to be solved optimally. Apart from the essential matrix, the algorithm is applied to the camera pose problem, providing an optimal algorithm. The approach has been implemented and tested on a number of both synthetically generated and real data sets with good performance.
Avdelning/ar
Publiceringsår
2009
Språk
Engelska
Sidor
64-79
Publikation/Tidskrift/Serie
International Journal of Computer Vision
Volym
82
Issue
1
Dokumenttyp
Artikel i tidskrift
Förlag
Springer
Ämne
- Mathematics
Nyckelord
- Global optimization
- Essential matrix
- Branch-and-bound algorithm
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 1573-1405