ROLL-SENSITIVE ONLINE CAMERA ORIENTATION DETERMINATION ON THE STRUCTURED ROAD
- 1State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China
- 2Electronic Information School, Wuhan University, China
Keywords: Camera Calibration, Roll-sensitive, Autonomous Vehicles, Inverse Perspective Mapping, Lane Detection
Abstract. Online camera calibration technology can estimate the pose of the camera onboard in real time, playing an important role in many fields such as HD map production and autonomous vehicles. Some researchers use one vanishing point (VP) to calculate the pitch and yaw angle of the onboard camera. However, this method assumes that the roll angle is zero, which is impractical because of the inevitable installation error. This paper proposes a novel online camera orientation determination method based on a longitudinal vanishing point without the zero-roll hypothesis. The orientation of the camera is determined in two steps: calculating the pitch and yaw angles according to vanishing point theory, and then obtaining the roll angle with lane widths constraint which is modeled as an optimization problem. To verify the effectiveness of our algorithm, we evaluated it on the nuScenes dataset. As a result, the rotation error of the roll and pitch angle can achieve 0.154° and 0.116° respectively. Also, we deployed our method in the “Tuyou”, an autonomous vehicle developed by Wuhan University, and then tested it in the urban structured road. Our proposed method can reconstruct the ground space accurately compared with previous methods with zero-roll hypothesis.