Efficient and accurate camera calibration technique for 3-D computer vision

In this paper we propose a new technique for calibrating a camera with very high accuracy and low computational cost. The geometric camera parameters considered include camera position, orientation, focal length, radial lens distortion, pixel size, and optical axis piercing point. With our method, the camera parameters to be estimated are divided into two parts: the radial lens distortion coefficient κ and a composite parameter vector c composed of all the above geometric camera parameters other than κ. Instead of using nonlinear optimization techniques, the estimation of κ is transformed into an eigenvalue problem of a 8 × 8 matrix. Our method is fast since it requires only linear computation. It is accurate since the effect of the lens distortion is considered and all the information contained in the calibration points is used. Computer simulation and real experiment have shown that the performance of our calibration method is better than that of the well-known method proposed by Tsai.