Camera self-calibration from bivariate polynomials derived from Kruppa's equations

被引:31
作者
Habed, A. [1 ]
Boufama, B. [1 ]
机构
[1] Univ Windsor, Sch Comp Sci, Windsor, ON N9B 3P4, Canada
关键词
three-dimensional metric reconstruction; camera self-calibration; Kruppa's equations;
D O I
10.1016/j.patcog.2007.12.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a new set of equations for the self-calibration of a moving camera with constant intrinsic parameters. Unlike most existing methods that require solving equations in three or more unknowns, the proposed equations are only bivariate. In particular, we show that the three scale factors appearing in the Kruppa's equations, that are due to a triplet of images, are not independent but rather closely related. This relationship is used to derive sextic bivariate polynomial equations and allow the recovery of the unknown scale factors using a homotopy continuation method. Once the scale factors are calculated, an estimate of Kruppa's coefficients can be linearly retrieved and then refined through a nonlinear least-squares optimization procedure. The results of our experiments conducted on simulated data as well as the three-dimensional structure reconstruction using real images are also presented in the paper. (c) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2484 / 2492
页数:9
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