Camera Calibration of Binocular Vision Based on Virtual 1D Target

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Abstract:

A field calibration method based on virtual 1D target is proposed for the extrinsic parameters of binocular vision. A target is placed on high precision 1D lifting platform to create virtual 1D target through motions of lifting platform. Two cameras are used to obtain virtual target images of different positions and preliminarily achieve extrinsic parameter calibration of binocular vision based on epipolar constraint equation. Finally, the length of virtual 1-D target is used to optimize the extrinsic parameters. This method is featured with easy operation, flexible application and field calibration. The experimental results verify the feasibility of this calibration method and show it can yield high field calibration precision.

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Periodical:

Advanced Materials Research (Volumes 605-607)

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859-863

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Online since:

December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Wei Sun, Long Chen, Bo Hu, Long Ren and Xianxiang Wu. Binocular Vision-based Position Determination Algorithm and System. 2012 International Conference on Computer Distributed Control and Intelligent Enviromental Monitoring. 2012:170-173.

DOI: 10.1109/cdciem.2012.47

Google Scholar

[2] Brojeshwar Bhowmick, Sambit Bhadra and Arijit Sinharay. Stereo Vision Based Pedestrians Detection and Distance Measurement for Automotive Application. 2011 Second International Conference on Intelligent Systems, Modelling and Simulation. 2011:25-29.

DOI: 10.1109/isms.2011.14

Google Scholar

[3] Guoqing Hu, Nicholas Gans and Warren Dixon. International Jounal of Robust and Nonlinear Control. 2010, 20:489-503.

Google Scholar

[4] Zhengyou Zhang. IEEE Transations on Pattern Analysis and Machine Intelligence. 2000, 22(11):1330-1334.

Google Scholar

[5] Zhengyou Zhang. IEEE Transations on Pattern Analysis and Machine Intelligence. 2004, 26(7):892-899.

Google Scholar

[6] Fei Qi, Qihe Li, Yupin Luo, Dongcheng Hu. Pattern Recognition. 2007, 40(6):1785-1792.

Google Scholar

[7] Zhen Yang, Junhua Sun, Ziyan Wu and Guangjun Zhang. Journal of Optoeletronics &Laser. 2010, 21(3):411-414. "In Chinese"

Google Scholar

[8] Junpeng Xue and Xianyu Su. Acta Optica Sinica. 2012, 32(1):1-7. "In Chinese"

Google Scholar

[9] Qiang Fu, Quan Quan and Kaiyuan Cai. Multi-camera Calibration Based on Freely Moving One Dimensional Object. Proceeding of the 30th Chinese Control Conference. 2011:5023-5028.

Google Scholar

[10] Qiaoyu Xu, Dong Ye and Rensheng Che. Acta Optica Sinica. 2008, 28(1):81-86. "In Chinese"

Google Scholar