Yamakawa Laboratory, The University of Tokyo

東京大学　山川研究室

We propose an online method for calibrating the orientation of cameras mounted on vehicles. To calibrate the orientation of the target camera relative to the vehicle, we propose using a high-speed vision sensor, focused on the ground, in conjunction with the target camera. First, the high-speed camera's planar motion parallel to ground plane and target camera's motion are estimated by a semi-dense approach and visual odometry method, respectively. Then, the motions are used to calibrate the target camera's orientation through nonlinear optimization based on the invariance constraint of the extrinsic parameters and the nonholonomic constraint of the vehicle. Unlike traditional methods, this approach does not depend on artificial features such as lane markings and utilizes ground information more efficiently, making it applicable in broader scenarios. Simulation and field tests have demonstrated that the target camera orientation calibration errors are approximately 1 degree, even on a bumpy road, affirming the accuracy and robustness of the proposed method.

The experiment data are available on Simulation test and field test data. (21GB)