DocumentCode :
3598548
Title :
Epipolar geometry estimation based on genetic algorithm under different strategies
Author :
Mingxing, Hu ; Qiang, Xing ; Baozong, Yuan ; Xiaofang, Tang
Author_Institution :
Inst. of Inf. Sci., Northern Jiaotong Univ., Beijing, China
Volume :
1
fYear :
2002
Firstpage :
885
Abstract :
The paper addresses the problem of robust fundamental matrix estimation employing a new method based on genetic algorithms under different strategies, which use each gene to stand for a pair of correspondences, take every chromosome as a minimum subset for epipolar geometry estimation, and compute the fundamental matrix according to the length of the chromosomes. The method eventually converges to a globally optimal solution and is relatively unaffected by outliers. Experiments with both synthetic data and real images show that our method is more robust and precise than other typical methods.
Keywords :
genetic algorithms; geometry; image processing; matrix algebra; parameter estimation; chromosomes; epipolar geometry estimation; fundamental matrix estimation; gene; genetic algorithm; globally optimal solution; perspective images; real images; stereo image processing; synthetic data; Biological cells; Computational geometry; Constraint theory; Equations; Genetic algorithms; Image converters; Information science; Layout; Noise robustness; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
Type :
conf
DOI :
10.1109/ICOSP.2002.1181198
Filename :
1181198
Link To Document :
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