Synchronization and calibration of camera networks from silhouettes

We propose an automatic approach to synchronize a network of uncalibrated and unsynchronized video cameras, and recover the complete calibration of all these cameras. In this paper, we extend recent work on computing the epipolar geometry from dynamic silhouettes, to deal with unsynchronized sequences and find the temporal offset between them. This is used to compute the fundamental matrices and the temporal offsets between many view-pairs in the network. Knowing the time-shifts between enough view-pairs allows us to robustly synchronize the whole network. The calibration of all the cameras is recovered from these fundamental matrices. The dynamic shape of the object can then be recovered using a visual-hull algorithm. Our method is especially useful for multi-camera shape-from-silhouette systems, as visual hulls can now be reconstructed without the need for a specific calibration session.

[1]  Robert C. Bolles,et al.  A RANSAC-Based Approach to Model Fitting and Its Application to Finding Cylinders in Range Data , 1981, IJCAI.

[2]  John Porrill,et al.  Curve matching and stereo calibration , 1991, Image Vis. Comput..

[3]  Sudipta N. Sinha,et al.  Camera network calibration from dynamic silhouettes , 2004, CVPR 2004.

[4]  Roberto Cipolla,et al.  Structure and motion from silhouettes , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[5]  Denis Simakov,et al.  Feature-Based Sequence-to-Sequence Matching , 2006, International Journal of Computer Vision.

[6]  Wojciech Matusik,et al.  Polyhedral Visual Hulls for Real-Time Rendering , 2001, Rendering Techniques.

[7]  Hai Tao,et al.  Dynamic depth recovery from unsynchronized video streams , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

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

[9]  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.