基于激光点云多条件约束的相机检校方法

为了克服相机检校对二维/三维检校场的依赖,提出一种基于激光点云多条件约束的相机检校方法。该方法通过对相机获取的多视影像进行光束法平差获得初始相机参数;利用影像点云与其最邻近的激光点云之间的位置关系,以共线方程为基础模型,建立多条件约束的相机检校数学模型;使用不等式约束的最小二乘方法平差迭代解算相机参数。将本文方法与基于三维控制场的检校精度进行了实验对比分析,结果表明本文方法与基于三维控制场的检校精度相当,两者反投影平均误差相差小于0.1 pixel,验证了本文方法在没有传统检校场的情况下进行相机检校的可行性。

Camera Calibration Method with Multi-condition Constraints Based on Laser Points

A camera calibration method based on multi-condition constraints of laser point cloud is proposed to overcome the dependence of camera calibration on the 2 D/3 D calibration field.The initial camera parameters are obtained by bundle adjustment from the multi-view image obtained by the camera.Then,based on the collinear equation,the mathematical model of the multi-condition constraints camera calibration is established by using the position relationship between the image point cloud and its nearest laser point cloud.Furthermore,the least square method with inequality constrains is used to calculate the camera parameters iteratively.The camera calibration accuracy of the method is compared with that of the3 D control field.The experiment results show that it is equivalent to the calibration accuracy based on the3 D control field.The average error difference between the two laser point cloud reflection is less than 0.1 pixel,which further verifies the feasibility of the method without traditional control field.