A linear self-calibration approach for camera focal length estimation

This paper comes up with a linear self-calibration approach for camera focal length estimation. Compared with other linear techniques, the advantage of this method is that no priori information of motion is needed. From the degenerated equations (one quadratic and two linear), the essential constraints are generated on calibration of camera intrinsic parameters. Thus the focal length of camera is conveniently obtained in closed form on the reliable assumption that only the focal length is unknown but constant, and the skew factor is zero. Synthetic object/image, real images of indoor and outdoor generic scenes and 3D model reconstruction are involved in our experiments to analyze the accuracy of the estimated focal length. The experimental results indicate that our proposed method is both robust and efficient.

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

[2]  Peter Sturm,et al.  On focal length calibration from two views , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[3]  Richard I. Hartley,et al.  Kruppa's Equations Derived from the Fundamental Matrix , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  S. Shankar Sastry,et al.  Kruppa Equation Revisited: Its Renormalization and Degeneracy , 2000, ECCV.

[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]  Lisa G. McIlrath Dynamic camera self-calibration from controlled motion sequences , 1993, CVPR.

[7]  Peter J. Rousseeuw,et al.  Robust Regression and Outlier Detection , 2005, Wiley Series in Probability and Statistics.

[8]  Alexandru Tupan,et al.  Triangulation , 1997, Comput. Vis. Image Underst..

[9]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[10]  Richard I. Hartley,et al.  Self-Calibration of Stationary Cameras , 1997, International Journal of Computer Vision.

[11]  S. P. Mudur,et al.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

[12]  Peter J. Rousseeuw,et al.  Robust regression and outlier detection , 1987 .

[13]  Michael Brady,et al.  Self-calibration of the intrinsic parameters of cameras for active vision systems , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Ashraf A. Kassim,et al.  Focal length self-calibration based on degenerated Kruppa's equations: method and evaluation , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[15]  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).