DocumentCode :
3614462
Title :
Line reconstruction from many perspective images by factorization
Author :
D. Matinec;T. Pajdla
Author_Institution :
Faculty of Elec. Eng, Czech Technical University in Prague, Czech Republic
Volume :
1
fYear :
2003
fDate :
6/25/1905 12:00:00 AM
Abstract :
This paper proposes a method for line reconstruction from many perspective images by factorization of a matrix containing line correspondences. No point correspondences are used. We formulate the reconstruction from line correspondences in the language of Plucker line coordinates. The reconstruction is posed as the factorization of 3m /spl times/ n matrix S into the product S = QL of 3m /spl times/ 6 projection matrix Q and 6 /spl times/ n line matrix L, both satisfying Klein identities. The matrix S contains coordinates of lines detected in perspective images. Similarly to reconstruction from point correspondences in perspective images, the matrix S has to be properly rescaled before it can be factorized. We propose a scaling of image line coordinates based on trifocal tensors that are analogical to the scaling proposed by Sturm and Triggs (1996) for points. We propose an SVD based factorization enforcing Klein identities on Q and L in a noise-free situation. We show experiments on real data that suggest that a good reconstruction may be obtained even if data is noisy and the identities are not enforced exactly. We also discuss an extension of the method for images with occlusions.
Keywords :
"Image reconstruction","Jacobian matrices","Cameras","Layout","Robustness","Cybernetics","Tensile stress","Geometry","Equations"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
ISSN :
1063-6919
Print_ISBN :
0-7695-1900-8
Type :
conf
DOI :
10.1109/CVPR.2003.1211395
Filename :
1211395
Link To Document :
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