DocumentCode :
532626
Title :
A new method for coplanar camera calibration based on neural network
Author :
Xiaobo, Chen ; Haifeng, Guo ; Yinghua, Yang ; Shukai, Qin
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Volume :
2
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
As an essential step of 3D reconstruction, research on the camera calibration methods has great important significance of theoretical study and practical value. In this paper, a new simply, flexible and more accurate coplanar camera calibration method is proposed based on neural network. This method only requires a coplanar target and without camera motion. The neural network is used to learn the relationships between the image information and the 3D information to amend aberrance of camera, and it neither requires the inner and outer parameters of the camera and any prior knowledge of the parameters. The experimental results of image simulation show that the proposed method is correct and effective.
Keywords :
aberrations; calibration; cameras; computer vision; image reconstruction; image sensors; neural nets; 3D reconstruction; aberrance emendation; computer vision; coplanar camera calibration; image information; image simulation; neural network; aberrance emendation; camera calibration; coplanar target; neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620854
Filename :
5620854
Link To Document :
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