Self-calibration of a 1D projective camera and its application to the self-calibration of a 2D projective camera

被引:39
|
作者
Faugeras, O
Quan, L
Strum, P
机构
[1] INRIA, F-06902 Sophia Antipolis, France
[2] CNRS, INRIA, ZIRST, F-38330 Montbonnot St Martin, France
关键词
vision geometry; camera model; self-calibration; planar motion; 1D camera;
D O I
10.1109/34.879801
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We introduce the concept of self-calibration of a 1D projective camera from point correspondences, and describe a method for uniquely determining the two internal parameters of a 1D camera, based on the trifocal tensor of three 1D images. The method requires the estimation of the trifocal tensor which can be achieved linearly with no approximation unlike the trifocal tensor of 2D images and solving for the roots of a cubic polynomial in one variable. Interestingly enough, we prove that a 2D camera undergoing planar motion reduces to a 1D camera. From this observation, we deduce a new method for self-calibrating a 2D camera using planar motions. Both the self-calibration method for a 1D camera and its applications for 2D camera calibration are demonstrated on real image sequences.
引用
收藏
页码:1179 / 1185
页数:7
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