DocumentCode :
3050256
Title :
Efficient iterative solution to M-view projective reconstruction problem
Author :
Chen, Qian ; Medioni, Gérard
Author_Institution :
Univ. of Southern California, Los Angeles, CA, USA
Volume :
2
fYear :
1999
fDate :
1999
Abstract :
We propose an efficient solution to the general M-view projective reconstruction problem, using matrix factorization and iterative least squares. The method can accept input with missing data, meaning that not all points are necessarily visible in all views. It runs much faster than the often-used non-linear minimization method, while preserving the accuracy of the latter. The key idea is to convert the minimization problem into a series of weighted least squares sub-problems with drastically reduced matrix sizes. Additionally, we show that good initial values can always be obtained. Experimental results on both synthetic and real data are presented. Potential applications are also demonstrated
Keywords :
image reconstruction; iterative methods; matrix decomposition; M-view projective reconstruction; iterative least squares; iterative solution; matrix factorization; Business; Cameras; Convergence; Jacobian matrices; Least squares methods; Matrix converters; Minimization methods; Reconstruction algorithms; Tensile stress; Transmission line matrix methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.
Conference_Location :
Fort Collins, CO
ISSN :
1063-6919
Print_ISBN :
0-7695-0149-4
Type :
conf
DOI :
10.1109/CVPR.1999.784608
Filename :
784608
Link To Document :
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