The Self-calibration of Varying Internal Camera Parameters Based on Image of Dual Absolute Quadric Transformation

This paper presents an method of self-calibration of varying internal camera parameters that based on image of dual absolute quadric transformation. Absolute dual quadric elements have so large differences in magnitude that solutions are extremely sensitive to noise.Through the transformation, all the elements of the image of dual absolute quadric are transformed into the same magnitude, So the solutions become more stable. The theorical analysis and experiments with both simulated and real data demonstrate that this self-calibration method can lead to an enormous improvement on the stability and robustness of the results without increasing computation.

[1]  Bill Triggs,et al.  Autocalibration and the absolute quadric , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  O. D. Faugeras,et al.  Camera Self-Calibration: Theory and Experiments , 1992, ECCV.

[3]  Anders Heyden,et al.  Euclidean reconstruction from image sequences with varying and unknown focal length and principal point , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Luc Van Gool,et al.  The modulus constraint: a new constraint self-calibration , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[5]  Reinhard Koch,et al.  Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[6]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[7]  Meng Xiao.  Recent Progress in Camera Self-Calibration , 2003 .

[8]  Hu Zhan-Yi.  A Linear Camera Self-Calibration Technique Based on Projective Reconstruction , 2002 .

[9]  Jong-Eun Ha,et al.  Initialization method for self-calibration using 2-views , 2005, Pattern Recognit..

[10]  Zhong Bo-tao.  Self-calibration technique based on Kruppa equations obtaining initial solution by translational motion , 2009 .

[11]  Olivier D. Faugeras,et al.  A theory of self-calibration of a moving camera , 1992, International Journal of Computer Vision.

[12]  Jiang Ze-tao.  Camera self-calibration method based on genetic algorithm , 2009 .

[13]  S. Bougnoux,et al.  From projective to Euclidean space under any practical situation, a criticism of self-calibration , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[14]  Richard I. Hartley,et al.  Projective Reconstruction and Invariants from Multiple Images , 1994, IEEE Trans. Pattern Anal. Mach. Intell..