Simplified Method for Joint Calibration of 3D Ladar and Monocular Camera
Simplified Method for Joint Calibration of 3D Ladar and Monocular Camera

To address the problem of data fusion between monocular camera image with 3D data from laser detection and ranging (LADAR) sensor, this paper proposes a novel simplified scheme based on the planar feature method, which can meet the accuracy requirements of the joint calibration with fewer checkerboard calibration plate (CP) positions than traditional methods. First, a mathematical model of the joint calibration is established to obtain the calibration parameters. Secondly, the selection of positions and orientations of the CP are introduced and the corresponding influence to the calibration is analyzed. Then, the calibration result is optimized by using a nonlinear Levenberg-Marquardt (LM) optimization approach, and the distance residual method is utilized to estimate the accuracy. Finally, experimental results conclude that the minimum number of positions required to meet the joint calibration accuracy in the proposed method is 5, which is less than 12 in traditional methods.
To address the problem of data fusion between monocular camera image with 3D data from laser detection and ranging (LADAR) sensor, this paper proposes a novel simplified scheme based on the planar feature method, which can meet the accuracy requirements of the joint calibration with fewer checkerboard calibration plate (CP) positions than traditional methods. First, a mathematical model of the joint calibration is established to obtain the calibration parameters. Secondly, the selection of positions and orientations of the CP are introduced and the corresponding influence to the calibration is analyzed. Then, the calibration result is optimized by using a nonlinear Levenberg-Marquardt (LM) optimization approach, and the distance residual method is utilized to estimate the accuracy. Finally, experimental results conclude that the minimum number of positions required to meet the joint calibration accuracy in the proposed method is 5, which is less than 12 in traditional methods.