Generic camera calibration and modeling using spline surfaces

Cameras are a commonly used sensor in advanced driver assistance systems (ADAS). They serve to get vast amounts of information about a vehicle's environment. To accurately localize the measured data in relation to the own car, exact camera calibration is a prerequisite. This includes extrinsic as well as intrinsic parameters. While many works in the area of ADAS focus on extrinsic calibration, this work covers the intrinsic calibration. We use a generic camera model which regards the viewing ray of every pixel separately and can therefore be used to describe arbitrary imaging devices even with massive lens distortions. As the calibration procedure works for any camera, only one method has to be implemented, which simplifies the sensor calibration process. Former works have shown the applicability of generic camera models but do not cover important practical aspects which are subpixel ray determination and forward projection of arbitrary 3d points to the image plane. Furthermore, the calibration processes described so far are cumbersome and prone to inaccuracies. We propose to use spline surfaces to simplify the calibration procedure and implement general back and forward projection. The applicability of our approach is proved by showing calibration results for various real cameras.