A NEW CAMERA SELF-CALIBRATION METHOD BASED ON CSA

被引:0
|
作者
Geng, Li-Chuan [1 ,2 ]
Li, Shao-Zi [1 ,2 ]
Su, Song-Zhi [1 ,2 ]
Cao, Dong-Lin [1 ,2 ]
Lei, Yun-Qi [3 ]
Ji, Rong-Rong [1 ,2 ]
机构
[1] Xiamen Univ, Dept Cognit Sci, Xiamen 361005, Fujian, Peoples R China
[2] Xiamen Univ, Fujian Key Lab Brainlike Intelligent Syst, Xiamen 361005, Fujian, Peoples R China
[3] Xiamen Univ, Dept Comp Sci, Xiamen 361005, Fujian, Peoples R China
基金
高等学校博士学科点专项科研基金;
关键词
Camera self-calibration; AIS; Kruppa equations; Fundamental Matrix; EQUATIONS;
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
A large number of computer vision applications rely on camera calibration, Camera self-calibration which only depends on the relationship between corresponding points of a pair of images draws much attention for its simplicity, Almost all the camera self-calibration methods rely on the solution of Kruppa equations which are difficult to be directly solved, The state-of-the-art self-calibration algorithms usually convert the solution of these equations to non-linear optimization problem, traditional optimization methods usually have the drawback of convergent to local extreme. Artificial immune system (AIS) has the ability to fast convergent to global extreme. To address this problem, we proposed an artificial immune system based method which can fast convergent to the global optimization solutions. We demonstrate the performance of the proposed method with synthetic and real data.
引用
收藏
页数:6
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