Fujipress Home | Search | About FINDER

Paper:
Language: English:

Determining Extrinsic Parameters for Active Stereovision


Huawei Wang and De Xu


Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China


Received: July 3, 2008

Accepted: January 15, 2009


Keywords: extrinsic parameters, active stereovision, calibration

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.13, No.2 pp. 76-79, 2009

Abstract



In the novel method we propose for determining extrinsic parameters for active stereovision, we first map the relationship between rotational and yaw angles based on least squares fitting, then optimize the rotational axis between two cameras using the Levenberg-Marquardt algorithm. Extrinsic parameters are then easily derived for active stereovision based on the mapping model without complex recalibration. The results of experiments confirmed our proposed method's feasibility.
preview Preview (PDF)  full text Full Text (PDF 247KB)

Reference

[1] R. Y. Tsai, “A versatile camera calibration technique for high accuracy 3D machine vision metrology using off the shelf TV cameras and lens,” IEEE Journal of Robotics Automation, Vol.3, No.4, pp. 323-344, 1987.

[2] Z. Zhang, “A flexible new technique for camera calibration,” IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol.22, No.11, pp. 1330-1334, 2000.

[3] S. Bougnoux, “From projective to Euclidean space under any practical situation, a criticism of self-calibration,” Proc. of the 6th Int. Conf. on Computer Vision, pp. 790-796, 1998.

[4] Q. T. Luong and O. Faugeras, “Self-calibration of a moving camera from point correspondences and fundamental matrices,” Int. Journal of Computer Vision, Vol.22, No.3, pp. 261-289, 1997.

[5] S. J. Maybank and O. Faugeras, “A theory of self-calibration of a moving camera,” Int. Journal of Computer Vision, Vol.8, No.2, pp. 123-151, 1992.

[6] M. Pagel, E. Mael, and C. Malsburg, “Self-calibration of the fixation movement of a stereo camera,” Machine Learning, Vol.31, No.13, pp. 169-186, 1998.

[7] H. Zou, Z. Gong, and J. Luo. “State of the art and trend of biomimetic eye,” Robot, Vol.27, No.5, pp. 469-474, 2005.

[8] H. J. Kim, M. H. Yoo, and S. W. Lee, “A control model for vergence movement on a stereo robotic head using disparity flux,” Proc. of the 15th Int. Conf. on Pattern Recognition, Vol.4, pp. 491-494, 2000.

[9] D. Xu, Y. F. Li, M. Tan, and Yang Shen, “A new active visual system for humanoid robots,” IEEE Transactions on System, Man & Cybernetics-Part B: Cybernetics, Vol.38, No.2, pp. 320-330, 2008.

[10] R. M Haralick, D. Lee, K. Ottenburg, and M. Nolle, “Analysis and solutions of the three point perspective pose estimation problem,” Proc. of the Int. Conf. on Computer Vision and Pattern Recognition, pp. 592-598, 1991.

[11] D. Dementhond, “Exact and approximate solutions of the perspective-3-point problem,” IEEE Transactions on pattern analysis and machine intelligence, Vol.14, No.11, pp. 1100-1105, 1992.

[Notice]
* "Preview" is the first 2 pages of the article. You don't need the registration.
* To read the PDF file you will then need to download and install the Adobe Reader.
Adobe Reader is free and available for download here:

adobe reader

Terms and Conditions | Privacy Policy | Recruit | Advertising Information | Contact Us