Linked Life Data

20431130

Source:http://linkedlifedata.com/resource/pubmed/id/20431130

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2010-4-30
pubmed:abstractText
We investigate the problem of estimating the ego-motion of a multicamera rig from two positions of the rig. We describe and compare two new algorithms for finding the 6 degrees of freedom (3 for rotation and 3 for translation) of the motion. One algorithm gives a linear solution and the other is a geometric algorithm that minimizes the maximum measurement error-the optimal L{infinity} solution. They are described in the context of the General Camera Model (GCM), and we pay particular attention to multicamera systems in which the cameras have nonoverlapping or minimally overlapping field of view. Many nonlinear algorithms have been developed to solve the multicamera motion estimation problem. However, no linear solution or guaranteed optimal geometric solution has previously been proposed. We made two contributions: 1) a fast linear algebraic method using the GCM and 2) a guaranteed globally optimal algorithm based on the L{infinity} geometric error using the branch-and-bound technique. In deriving the linear method using the GCM, we give a detailed analysis of degeneracy of camera configurations. In finding the globally optimal solution, we apply a rotation space search technique recently proposed by Hartley and Kahl. Our experiments conducted on both synthetic and real data have shown excellent results.
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:month
Jun
pubmed:issn
1939-3539
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
32
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1044-59
pubmed:year
2010
pubmed:articleTitle
Motion estimation for nonoverlapping multicamera rigs: linear algebraic and L{infinity} geometric solutions.
pubmed:affiliation
Department of Computer Science, Queen Mary, University of London, Mile End Road, London E14NS, United Kingdom. jaehak@dcs.qmul.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't