Robust unambiguous parametrization of the essential manifold

被引:0
|
作者
Subbarao, Raghav [1 ,2 ]
Genc, Yakup [2 ]
Meer, Peter [1 ]
机构
[1] Rutgers State Univ, ECE Dept, Piscataway, NJ 08854 USA
[2] Siemens Corp Res, Real Time Vis & Modelling Dept, Princeton, NJ 08540 USA
来源
2008 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-12 | 2008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
Analytic manifolds were recently used for motion averaging, segmentation and robust estimation. Here we consider the epipolar constraint for calibrated cameras, which is the most general motion model for calibrated cameras and is encoded by the essential matrix. The set of all essential matrices forms the essential manifold. We provide a theoretical characterization of the geometry of the essential manifold and develop a parametrization which associates each essential matrix with a unique point on the manifold. Our work provides a more complete theoretical analysis of the essential manifold than previous work in this direction. We show the results of using this parametrization with real data sets, while previous work concentrated on theoretical analysis with synthetic data.
引用
收藏
页码:2704 / +
页数:2
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