Stereo Autocalibration from One Plane

This paper describes a method for autocalibrating a stereo rig. A planar object performing general and unknown motions is observed by the stereo rig and, based on point correspondences only, the autocalibration of the stereo rig is computed. A stratified approach is used and the autocalibration is computed by estimating first the epipolar geometry of the rig, then the plane at infinity Π∞ (affine calibration) and finally the absolute conic Ω∞ (Euclidean calibration). We show that the affine and Euclidean calibrations involve quadratic constraints and we describe an algorithm to solve them based on a conic intersection technique. Experiments with both synthetic and real data are used to evaluate the performance of the method.

[1]  A. Heyden,et al.  Euclidean reconstruction from constant intrinsic parameters , 1996, Proceedings of 13th International Conference on Pattern Recognition.

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

[3]  I. Reid,et al.  Metric calibration of a stereo rig , 1995, Proceedings IEEE Workshop on Representation of Visual Scenes (In Conjunction with ICCV'95).

[4]  Richard I. Hartley,et al.  Euclidean Reconstruction from Uncalibrated Views , 1993, Applications of Invariance in Computer Vision.

[5]  J. G. Semple,et al.  Algebraic Projective Geometry , 1953 .

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

[7]  Richard I. Hartley,et al.  In defence of the 8-point algorithm , 1995, Proceedings of IEEE International Conference on Computer Vision.

[8]  Rachid Deriche,et al.  A Robust Technique for Matching two Uncalibrated Images Through the Recovery of the Unknown Epipolar Geometry , 1995, Artif. Intell..

[9]  Luc Van Gool,et al.  A stratified approach to metric self-calibration , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Radu Horaud,et al.  Self-calibration and Euclidean reconstruction using motions of a stereo rig , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[11]  Q. Luong,et al.  Canonic representations for the geometries of project views , 1993 .

[12]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Olivier D. Faugeras,et al.  From projective to Euclidean reconstruction , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Thierry Viéville,et al.  Canonic Representations for the Geometries of Multiple Projective Views , 1994, ECCV.

[15]  O. Faugeras Stratification of three-dimensional vision: projective, affine, and metric representations , 1995 .

[16]  Antonio Criminisi,et al.  Creating Architectural Models from Images , 1999, Comput. Graph. Forum.

[17]  O. Faugeras Three-dimensional computer vision: a geometric viewpoint , 1993 .

[18]  Thomas S. Huang,et al.  Theory of Reconstruction from Image Motion , 1992 .

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

[20]  Bill Triggs,et al.  Autocalibration from Planar Scenes , 1998, ECCV.

[21]  Stephen J. Maybank,et al.  On plane-based camera calibration: A general algorithm, singularities, applications , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).