Active Self-calibration of Multi-camera Systems

We present a method for actively calibrating a multicamera system consisting of pan-tilt zoom cameras. After a coarse initial calibration, we determine the probability of each relative pose using a probability distribution based on the camera images. The relative poses are optimized by rotating and zooming each camera pair in a way that significantly simplifies the problem of extracting correct point correspondences. In a final step we use active camera control, the optimized relative poses, and their probabilities to calibrate the complete multi-camera system with a minimal number of relative poses. During this process we estimate the translation scales in a camera triangle using only two of the three relative poses and no point correspondences. Quantitative experiments on real data outline the robustness and accuracy of our approach.

[1]  Roger Y. Tsai,et al.  A new technique for fully autonomous and efficient 3D robotics hand/eye calibration , 1988, IEEE Trans. Robotics Autom..

[2]  Joachim Denzler,et al.  Self-calibration with Partially Known Rotations , 2007, DAGM-Symposium.

[3]  Philipp Slusallek,et al.  Wide area camera calibration using virtual calibration objects , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[4]  David Nistér,et al.  An efficient solution to the five-point relative pose problem , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

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

[7]  Richard I. Hartley.  Self-Calibration from Multiple Views with a Rotating Camera , 1994, ECCV.

[8]  Jan-Olof Eklundh,et al.  Computer Vision — ECCV '94 , 1994, Lecture Notes in Computer Science.

[9]  Joachim Denzler,et al.  Geometric and probabilistic image dissimilarity measures for common field of view detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[11]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[12]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[13]  T. Läbe.  AUTOMATIC RELATIVE ORIENTATION OF IMAGES , 2006 .

[14]  J. Tukey,et al.  Variations of Box Plots , 1978 .

[15]  Luc Van Gool,et al.  ViRoom - Low Cost Synchronized Multicamera System and Its Self-calibration , 2002, DAGM-Symposium.

[16]  Marc Pollefeys,et al.  Towards calibrating a pan-tilt-zoom camera network , 2004 .

[17]  Joachim Denzler,et al.  Global Uncertainty-based Selection of Relative Poses for Multi Camera Calibration , 2008, BMVC.

[18]  Paul Chippendale,et al.  Collective calibration of active camera groups , 2005, IEEE Conference on Advanced Video and Signal Based Surveillance, 2005..

[19]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.