The essential/fundamental matrix estimation as a constrained total least squares problem: Theory

被引：0
|
作者：
Cirrincione, G [1 ]
Cirrincione, M [1 ]
Van Huffel, S [1 ]
机构：
[1] Katholieke Univ Leuven, COSIC, SISTA, ESAT, B-3001 Louvain, Belgium
来源：
PROCEEDINGS OF THE FIFTH JOINT CONFERENCE ON INFORMATION SCIENCES, VOLS 1 AND 2 | 2000年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The essential matrix approach is a well-known technique in computer vision for recovering the motion and scene parameters from a sequence of images. This approach has long been considered as suboptimal because of the underestimation of the effect of noise. This paper interprets this method as a structured Total Least Squares problem. This novel viewpoint justifies the nonlinear gradient method [9] and extends it.
引用
收藏
页码：A409 / A412
页数：4
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