Abstract
A simple method for multiple camera calibration based on a novel geometric derivation is presented. The main advantage of this method is that it uses only three points in the world coordinate system to achieve the calibration. Rotation matrix and translation vector for each camera coordinate system are obtained via the given distance between the vertices of the marker triangle formed by the three points. Therefore, the different views from the different cameras can be converted into one top view in the world coordinate system. Eventually, the different trajectories traced by certain tracked agents on the floor plane can be obtained from different viewpoints and can be matched in a joint scene plane.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Y. I. Abdel-Aziz, and H.M. Karara, “Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry”, Proc, of the ASP Symposium on Close-Range Potogrammetry, pp. 1–18, 1971.
Tsai, R., “A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses, IEEE J. Robot. Autom., Vol. 3 pp. 323–344, 1987.
Zhang, Z, “A flexible new technique for camera calibration, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 22 pp. 1330–1334, 2000.
Sturm, P., and Maybank, S., “On plane-based camera calibration: A general algorithm, singularities, applications, IEEE CVPR, pp. 432–437, 1999.
Lucchese, L., “Geometric calibration of digital cameras through multiview rectification, Image Vis. Comput, Vol. 23 pp. 517–539, 2005.
Lee, L., Romano, R., Wang, L., and Stein, G., “Monitoring activities from multiple video streams: Establishing a common coordinate frame, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 22 pp. 758–767, 2000.
Cai, Q., and Aggarwal, J. K., “Human motion in structured environments using a distributed camera system, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 21 pp. 1241–1247, 1999.
Chang, T.-H., and Gong, S., “Tracking multiple people with a multi-camera system, IEEE Workshop Multi-Object Tracking, pp. 19–26, 2001.
Haralick, R., Lee, C., Ottenberg, K., Nolle, M., “Review and Analysis of Solutions of the Three Point Perspective Pose Estimation Problem, International Journal of Computer Vision, Vol. 13 pp. 331–356 1994.
Nister, D., “A minimal solution to the generalized 3-point pose problem. On planebased camera calibration A general algorithm, singularities, applications, IEEE CVPR Volume 1 pp. 1560–1567 2004.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mozerov, M., Amato, A., Al Haj, M., Gonzàlez, J. (2007). A Simple Method of Multiple Camera Calibration for the Joint Top View Projection. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_21
Download citation
DOI: https://doi.org/10.1007/978-3-540-75175-5_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75174-8
Online ISBN: 978-3-540-75175-5
eBook Packages: EngineeringEngineering (R0)