准确标定摄像机的混合粒子群优化方法

Hybrid Particle-Swarm-Optimization Method for Accurately Calibrating Cameras

摄像机标定在机器视觉系统研究中占据十分重要的部分,为更好更快地标定摄像机,提出一种基于混合粒子群算法的摄像机参数优化方法。用最小二乘法求出摄像机的内外参数,并以此作为待优化参数的初始值;然后以最小距离准则建立目标函数,再利用混合粒子群算法对摄像机参数进一步优化计算,最终获得误差小的摄像机参数。实验结果表明混合粒子群优化算法能够快速、高精度地收敛,可在一定程度上提高摄像机的标定精度。

Camera calibration is a very important part in machine-vision-system research.To calibrate a camera better and faster,we propose a camera-parameter-optimization method based on hybrid particle-swarm optimization.First,we obtain the internal and external parameters of the camera by the least-squares method and use them as the initial values of the parameters to be optimized.Then,we establish the objective function using the minimumdistance criterion.Next,we use a hybrid particle-swarm optimization algorithm to further optimize the camera parameters,and finally we obtain the camera parameters with only small errors.Our experimental results show that the optimization algorithm can converge quickly and accurately.Therefore,this method is able to improve cameracalibration accuracy of the camera to some extent.