Practical camera auto-calibration based on object appearance and motion for traffic scene visual surveillance

Camera calibration, as a fundamental issue in computer vision, is indispensable in many visual surveillance appli-cations. Firstly, calibrated camera can help to deal with perspective distortion of object appearance on image plane. Secondly, calibrated camera makes it possible to recover metrics from images which are robust to scene or view an-gle changes. In addition, with calibrated cameras, we can make use of prior information of 3D models to estimate 3D pose of objects and make object detection or tracking more robust to noise and occlusions. In this paper, we propose an automatic method to recover camera models from traffic scene surveillance videos. With only the camera height H measured, we can completely re-cover both intrinsic and extrinsic parameters of cameras based on appearance and motion of objects in videos. Ex-periments are conducted in different scenes and experimen-tal results demonstrate the effectiveness and practicability of our approach, which can be adopted in many traffic scene surveillance applications. 1