Self-Calibration and Metric Reconstruction Inspite of Varying and Unknown Intrinsic Camera Parameters

In this paper the theoretical and practical feasibility of self-calibration in the presence of varying intrinsic camera parameters is under investigation. The paper's main contribution is to propose a self-calibration method which efficiently deals with all kinds of constraints on the intrinsic camera parameters. Within this framework a practical method is proposed which can retrieve metric reconstruction from image sequences obtained with uncalibrated zooming/focusing cameras. The feasibility of the approach is illustrated on real and synthetic examples. Besides this a theoretical proof is given which shows that the absence of skew in the image plane is sufficient to allow for self-calibration. A counting argument is developed which—depending on the set of constraints—gives the minimum sequence length for self-calibration and a method to detect critical motion sequences is proposed.

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

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

[3]  Paul A. Beardsley,et al.  Euclidean Structure from Uncalibrated Images , 1994, BMVC.

[4]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[5]  Andrew Zisserman,et al.  Applications of Invariance in Computer Vision , 1993, Lecture Notes in Computer Science.

[6]  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).

[7]  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.

[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]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

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

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

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

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

[15]  Luc Van Gool,et al.  Euclidean 3D Reconstruction from Image Sequences with Variable Focal Lenghts , 1996, ECCV.

[16]  Lutz Falkenhagen Hierarchical Block-Based Disparity Estimation Considering Neighbourhood Constraints , 1997 .

[17]  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.

[18]  Reinhard Koch,et al.  Automatische Oberflächenmodellierung starrer dreidimensionaler Objekte aus stereoskopischen Rundum-Ansichten , 1997 .

[19]  Luc Van Gool,et al.  Self-Calibration from the Absolute Conic on the Plane at Infinity , 1997, CAIP.

[20]  Olivier D. Faugeras,et al.  Oriented Projective Geometry for Computer Vision , 1996, ECCV.

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

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

[23]  W. Clem Karl,et al.  Reconstructing Ellipsoids from Projections , 1994, CVGIP Graph. Model. Image Process..

[24]  Reinhard Koch,et al.  Multi Viewpoint Stereo from Uncalibrated Video Sequences , 1998, ECCV.

[25]  Peter F. Sturm,et al.  Critical motion sequences for monocular self-calibration and uncalibrated Euclidean reconstruction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.