Title :
Camera calibration using geometric constraints
Author :
Kearney, J.K. ; Yang, Xiaoli ; Zhang, Shenzhi
Author_Institution :
Dept. of Comput. Sci., Iowa Univ., IA, USA
Abstract :
A method to estimate the intrinsic and extrinsic patterns of a camera model is presented. The intrinsic parameters of camera center and focal length are estimated with a calibration device which is adjusted iteratively with four independent motions. Experimentation demonstrates that inexperienced users rapidly converge to satisfactory estimates. Extrinsic parameters define the position and orientation of the camera in a world coordinate frame. The straightforward formulation of this mapping leads to a complex system of nonlinear equations. Solutions based on nonlinear estimation techniques used unconstrained sets of known target points. These methods may converge to an incorrect solution and are characteristically ill-conditioned. By imposing a simple regularity on the arrangement of calibration points, the problem can be decomposed into a series of simple one- or two-parameter linear equations. The approach is described, and empirical tests of the accuracy of the method are given
Keywords :
calibration; cameras; computer vision; parameter estimation; accuracy; camera center; computer vision; extrinsic patterns; focal length; geometric constraints; intrinsic patterns; linear equations; nonlinear estimation techniques; orientation; parameter estimation; position; world coordinate frame; Calibration; Cameras; Computer science; Distance measurement; Glass; Image processing; Motion estimation; Nonlinear equations; Parameter estimation; Testing;
Conference_Titel :
Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-8186-1952-x
DOI :
10.1109/CVPR.1989.37918