基于主动视觉的摄像机自标定方法

CAMERA SELF CALIBRATION TECHNIQUE BASED ON ACTIVE VISION

  • 摘要: 摄像机标定是计算机视觉的一项基本任务.目前基于主动视觉的摄像机内参数自标定方法可分为两类:第一类方法是通过摄像机在三维空间内作两组平移运动,来求解摄像机内参数.第二类是由Basu,Du,和Hartley等人提出的通过摄像机旋转,求解摄像机内参数方法.后者在实际应用中存在严重不足,由于它要求摄像机只绕光源中心旋转,不能有任何平移,而在工程实践中摄像机光源中心难以测定,其旋转也难以保证无任何平移,因此难以实用.本文提出的摄像机标定方法属于前一类方法.与以往方法相比,它不要求摄像机作多组相互正交的平移运动,只要能准确测定出摄像机相对于初始位置三次线性独立平移运动的平移矢量,即可线性求解出摄像机内参数.理论证明,解存在且唯一.数值模拟表明该方法具有较强的鲁棒性,最后给出了采用真实图像的实验结果.

     

    Abstract: Camera calibration is one of the fundamental issues in computer vision.At present,camera self calibration techniques based on active vision fall into two species: the first one requires camera to translate along three dimensional directions many times,so that the camera intrinsic parameters can be solved.The second one requires camera to rotate.Because the second requires camera to have no translation while it rotates,it is very difficult to fulfil this requirement in practice.In this paper,a new camera self calibration technique is proposed.It belongs to the first method.Unlike the former methods,our approach doesn′t require camera to translate along two orthogonal directions many times.If the camera is controlled to translate three times and the translation vectors are linear independent,the camera intrinsic parameters can be solved through pseudo inverse matrix theory.The analysis shows that the solution is existing and unique,and the important result has been proved.Tests with synthetic data and real images indicate that the algorithm is robust and practical.

     

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