Determining the epipolar geometry and its uncertainty: A review

被引:1039
作者
Zhang, ZY [1 ]
机构
[1] INRIA, F-06902 Sophia Antipolis, France
关键词
epipolar geometry; fundamental matrix; calibration; reconstruction; parameter estimation; robust techniques; uncertainty characterization; performance evaluation; software;
D O I
10.1023/A:1007941100561
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
Two images of a single scene/object are related by the epipolar geometry, which can be described by a 3 x 3 singular matrix called the essential matrix if images' internal parameters are known, or the fundamental matrix otherwise. It captures all geometric information contained in two images, and its determination is very important in many applications such as scene modeling and vehicle navigation. This paper gives an introduction to the epipolar geometry, and provides a complete review of the current techniques for estimating the fundamental matrix and its uncertainty. A well-founded measure is proposed to compare these techniques. Projective reconstruction is also reviewed. The software which we have developed for this review is available on the Internet.
引用
收藏
页码:161 / 195
页数:35
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