DocumentCode :
2732591
Title :
Camera calibration from multiple views of a 2D object, using a global nonlinear minimization method
Author :
Devy, M. ; Garric, V. ; Orteu, J.J.
Author_Institution :
Lab. d´´Autom. et d´´Anal. des Syst., CNRS, Toulouse, France
Volume :
3
fYear :
1997
fDate :
7-11 Sep 1997
Firstpage :
1583
Abstract :
An important task in most 3D vision systems is camera calibration. Many camera models, numerical methods and experimental set-ups have been proposed in the literature to solve the calibration problem. We have analysed and tried many methods, and we conclude that the main problems lie in the choice of the numerical methods and on the calibration object. We propose in this paper a method which is based on a camera model that incorporates lens distortion, and involves a nonlinear minimization technique which can be performed using multiple views of a single 2D object and subpixel feature extraction. We present an application for which only a 2D calibration object can be used
Keywords :
calibration; computer vision; feature extraction; minimisation; stereo image processing; video cameras; 2D object; 3D vision systems; camera calibration; computer vision; feature extraction; global nonlinear minimization; lens distortion; numerical methods; Calibration; Cameras; Feature extraction; Lenses; Minimization methods; Nonlinear distortion; Nonlinear optics; Optical distortion; Performance evaluation; Transmission line matrix methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference on
Conference_Location :
Grenoble
Print_ISBN :
0-7803-4119-8
Type :
conf
DOI :
10.1109/IROS.1997.656569
Filename :
656569
Link To Document :
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