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Global Optimization through Rotation Space Search

Hartley, Richard; Kahl, Fredrik

Description

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...[Show more]

dc.contributor.authorHartley, Richard
dc.contributor.authorKahl, Fredrik
dc.date.accessioned2015-12-10T22:15:44Z
dc.identifier.issn0920-5691
dc.identifier.urihttp://hdl.handle.net/1885/50831
dc.description.abstractThis 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.
dc.publisherSpringer
dc.sourceInternational Journal of Computer Vision
dc.subjectKeywords: Algorithms; Cameras; Cellular radio systems; Computer vision; Convex optimization; Global optimization; Image processing; Optimal systems; Optimization; Rotation; Algorithmic techniques; Branch and bounds; Branch-and-bound algorithm; Camera orientations; Branch-and-bound algorithm; Essential matrix; Global optimization
dc.titleGlobal Optimization through Rotation Space Search
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume82
dc.date.issued2009
local.identifier.absfor080104 - Computer Vision
local.identifier.ariespublicationu4334215xPUB211
local.type.statusPublished Version
local.contributor.affiliationHartley, Richard, College of Engineering and Computer Science, ANU
local.contributor.affiliationKahl, Fredrik , Lund University
local.description.embargo2037-12-31
local.bibliographicCitation.issue1
local.bibliographicCitation.startpage64
local.bibliographicCitation.lastpage79
local.identifier.doi10.1007/s11263-008-0186-9
dc.date.updated2016-02-24T10:59:09Z
local.identifier.scopusID2-s2.0-59149100446
local.identifier.thomsonID000262986100004
CollectionsANU Research Publications

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