DocumentCode :
2312703
Title :
Least-squares solution of absolute orientation with non-scalar weights
Author :
Hill, A. ; Cootes, T.F. ; Taylor, C.J.
Author_Institution :
Dept. of Med. Biophys., Univ. of Manchester Inst. of Sci. & Technol., UK
Volume :
1
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
461
Abstract :
The absolute orientation problem involves finding the Euclidean transformation which minimises the sum of the squared errors between two pointsets. In the standard form of the problem a confidence may be attached to each of the errors via a set of positive scalar weights. In this paper we consider a generalisation of the standard problem in which the components of the error vectors are coupled via a set of weight matrices. We show how problems of this type arise and derive two distinct forms of the problem. We present a closed-form solution to the first form of the 3-D problem and iterative solutions to the second form of the 2-D problem and both forms of the 3-D problem
Keywords :
computer vision; iterative methods; least squares approximations; matrix algebra; minimisation; 2-D problem; 3-D problem; Euclidean transformation; absolute orientation; closed-form solution; confidence; error vectors; iterative solutions; least-squares solution; nonscalar weights; weight matrices; Application software; Biophysics; Closed-form solution; Computer vision; Covariance matrix; Equations; Matrix decomposition; Quaternions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.546069
Filename :
546069
Link To Document :
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