基于入侵性杂草算法的摄像机标定过程优化

Camera Intrinsic Parameter Calibration Based on Invasive Weed Optimization Algorithm

双目视觉三维重建中使用摄像机作为校准工具对目标进行反馈,需要对摄像机的参数进行标定。为提高双目视觉技术中摄像机标定参数的精确度,提出一种基于入侵性杂草优化算法的摄像机标定方法。给出了利用入侵性杂草算法进行摄像机参数标定的具体步骤。分别对原有算法与入侵性杂草算法优化摄像机标定参数的过程进行了仿真,得到优化后的参数对比与最佳适应度函数。仿真结果表明,与原有算法优化过程相比,提出的标定方法得到了更准确的角点和更精确的参数,达到了提高标定精确度的目标。

The camera is used as the calibration tool to feed the target back in the binocular vision 3D reconstruction, and the camera parameters need to be calibrated. In order to improve the accuracy of the calibrated camera intrinsic parameter in the binocular vision technology, this paper proposed a camera intrinsic parameter calibration based on invasive weed optimization algorithm. The specific steps of the camera parameter calibration based on IWO algorithm was provided, and the simulation experiments of the camera parameter calibration process respectively based on the original algorithm and the IWO algorithm were conducted, getting the contrast of the optimized parameters and the function of the best fitness. The simulation results show that the camera parameter calibration based on IWO algorithm can get more accurate angular point and more accurate parameters compared with the original algorithm, and the goal of improving the calibration accuracy is achieved.