Robust epipolar geometry estimation using genetic algorithm

被引:23
作者
Chai, JX [1 ]
De Ma, S [1 ]
机构
[1] Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100080, Peoples R China
基金
中国国家自然科学基金;
关键词
epipolar geometry; robust parameter estimation; genetic algorithm; random sample;
D O I
10.1016/S0167-8655(98)00032-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Epipolar geometry is an important constraint to establish the correspondences in stereo vision. The 3 x 3 fundamental matrix describes the epipolar geometry between two uncalibrated images. In this paper, we formulate the epipolar geometry estimation as a global optimization problem, and then we present a genetic algorithm for parameter searching. Experiments with simulated and real data show that our algorithm performs very well in terms of robustness to outliers, rate of convergence and quality of the final estimation. (C) 1998 Published by Elsevier Science B.V. All rights reserved.
引用
收藏
页码:829 / 838
页数:10
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