A new constraint on the imaged absolute conic from aspect ratio and its application

Camera self-calibration is an important task in computer vision. In the literature, if the aspect ratio is known, people need additionally zero-skew-assumption to generate a constraint on the image of the absolute conic for camera calibration. However usually camera skew is nonzero and unknown. In this paper, a new quadric constraint on the image of the absolute conic is introduced, which is solely from known aspect ratio. Its application to single-view-based calibration and reconstruction is reported to illustrate its applicability and usefulness. In addition, the new constraint is experimentally shown to be advantageous over the commonly used zero-skew-based constraint in terms of calibration accuracy.

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

[2]  Reinhard Koch,et al.  Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters , 1999, International Journal of Computer Vision.

[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]  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).

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

[6]  Andrew W. Fitzgibbon,et al.  Automatic 3D Model Construction for Turn-Table Sequences , 1998, SMILE.

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

[8]  Long Quan,et al.  Single Axis Geometry by Fitting Conics , 2002, ECCV.

[9]  Andrew Zisserman,et al.  Self-Calibration from Image Triplets , 1996, ECCV.

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

[11]  Ian D. Reid,et al.  Single View Metrology , 2000, International Journal of Computer Vision.

[12]  Long Quan,et al.  Geometry of Single Axis Motions Using Conic Fitting , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Olivier D. Faugeras,et al.  Self-Calibration of a 1D Projective Camera and Its Application to the Self-Calibration of a 2D Projective Camera , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Quang-Tuan Luong,et al.  Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices , 1997, International Journal of Computer Vision.

[15]  Huang Feng A New Method on Single View Metrology , 2004 .

[16]  Andrew Zisserman,et al.  Multiple view geometry in computer visiond , 2001 .

[17]  Antonio Criminisi,et al.  Accurate Visual Metrology from Single and Multiple Uncalibrated Images , 2001, Distinguished Dissertations.

[18]  Zhanyi Hu,et al.  Camera Calibration from the Quasi-affine Invariance of Two Parallel Circles , 2004, ECCV.

[19]  Olivier D. Faugeras,et al.  Self-Calibration of a 1D Projective Camera and Its Application to the Self-Calibration of a 2D Projective Camera , 1998, ECCV.