Self-Calibration from the Absolute Conic on the Plane at Infinity

To obtain a metric reconstruction from images the cameras have to be calibrated. In recent years different approaches have been proposed to avoid explicit calibration. In this paper a new method is proposed which is closely related to some of the existing methods. Some interesting relations between the methods are uncovered. The method proposed in this paper shows some clear advantages. Besides some synthetic experiments a metric model is extracted from a video sequence to illustrate the feasibility of the approach.

[1]  O. Faugeras,et al.  Camera Self-Calibration from Video Sequences: the Kruppa Equations Revisited , 1996 .

[2]  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.

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

[4]  Olivier D. Faugeras,et al.  A comparison of projective reconstruction methods for pairs of views , 1995, Proceedings of IEEE International Conference on Computer Vision.

[5]  Olivier D. Faugeras,et al.  What can be seen in three dimensions with an uncalibrated stereo rig , 1992, ECCV.

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

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

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

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

[10]  Paul A. Beardsley,et al.  3D Model Acquisition from Extended Image Sequences , 1996, ECCV.

[11]  Richard I. Hartley,et al.  Estimation of Relative Camera Positions for Uncalibrated Cameras , 1992, ECCV.