DocumentCode
2698668
Title
Robust self-calibration and Euclidean reconstruction via affine approximation
Author
Kahl, Fredrik ; Heyden, Anders
Author_Institution
Dept. of Math., Lund Univ., Sweden
Volume
1
fYear
1998
fDate
16-20 Aug 1998
Firstpage
56
Abstract
A new approach to self-calibration and Euclidean reconstruction from image sequences is presented. The key idea is to start with the affine camera model as a first approximation to obtain the affine 3D structure. It is then upgraded to an Euclidean structure and finally, refined by applying the full perspective camera model and bundle adjustment. The proposed scheme makes no assumption about the scene nor the camera motion. The only assumption required is that the camera has zero skew, which is a minimal condition in order to self-calibrate the camera. However, if other information is available about the camera, it can and should be incorporated. The method is robust and it also provides an estimate of the accuracy of the estimated parameters. Experiments are presented to illustrate the performance of the approach
Keywords
approximation theory; calibration; computer vision; image reconstruction; image sequences; self-adjusting systems; Euclidean reconstruction; affine 3D structure; affine approximation; affine camera model; computer vision; image reconstruction; image sequences; self-calibration; Cameras; Image reconstruction; Image sequences; Layout; Matrix decomposition; Parameter estimation; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location
Brisbane, Qld.
ISSN
1051-4651
Print_ISBN
0-8186-8512-3
Type
conf
DOI
10.1109/ICPR.1998.711078
Filename
711078
Link To Document