A methodology for precise camera calibration for data collection applications in urban traffic scenes

Camera calibration is a necessary step in all video analysis applications to recover the real-world positions of concerned road users. Camera calibration can be performed based on feature correspondences between the real-world space and image space. In urban traffic scenes, the field of view may be too limited or video camera may not be accessible to allow reliable calibration based on vanishing points. A review of the current methods for camera calibration reveals little attention to these practical challenges that arise when studying urban intersections to support applications in traffic engineering. This study presents the development details of a robust camera calibration approach based on integrating a collection of geometric information found in urban traffic scenes in a consistent optimization framework. The developed approach was tested on six datasets obtained from urban intersections in British Columbia, California, and Kentucky. The results clearly demonstrated the robustness of the proposed approach.