High precision two-step calibration method for the fish-eye camera.

Fish-eye cameras are widely used on many occasions due to their ultrawide field of view (about 180°). In this paper, we present a high-precision two-step calibration method to calibrate fish-eye cameras. The two steps are the global polynomial projection model fitting and local line-fitting calibration optimization. In the first step, we obtain the projection model of the fish-eye camera and apply a quartic polynomial to fit the projection model over the entire image. In the second step, the fish-eye image is partitioned into several sections and line fitting is adopted in each section in order to further reduce the residual error of the first calibration step. Experiments show that the new method is able to correct the distortion of the real scene image well. In addition, its average reprojection error is 0.15 pixel better than 0.40 pixel of the general projection model described. The reason that higher calibration precision is obtained is that this method not only considers the global projection model of the fish-eye camera but also considers the local characteristics, such as small tangential distortion and asymmetry.

[1]  T. J. Herbert Calibration of fisheye lenses by inversion of area projections. , 1986, Applied optics.

[2]  H. Bakstein,et al.  Panoramic mosaicing with a 180/spl deg/ field of view lens , 2002, Proceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02.

[3]  B. Caprile,et al.  Using vanishing points for camera calibration , 1990, International Journal of Computer Vision.

[4]  Ernest L. Hall,et al.  Techniques for fisheye lens calibration using a minimal number of measurements , 2000, SPIE Optics East.

[5]  Jake K. Aggarwal,et al.  Intrinsic parameter calibration procedure for a (high-distortion) fish-eye lens camera with distortion model and accuracy estimation , 1996, Pattern Recognit..

[6]  Daniel E. Stevenson,et al.  Robot aerobics: four easy steps to a more flexible calibration , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  Junxiong Tang,et al.  High-accuracy angle detection for ultra-wide-field-of-view acquisition in wireless optical links , 2008 .

[8]  Roland Siegwart,et al.  A Toolbox for Easily Calibrating Omnidirectional Cameras , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Paul R. Cohen,et al.  Camera Calibration with Distortion Models and Accuracy Evaluation , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  D. F. Watson Computing the n-Dimensional Delaunay Tesselation with Application to Voronoi Polytopes , 1981, Comput. J..

[11]  Aly A. Farag,et al.  Nonmetric calibration of camera lens distortion: differential methods and robust estimation , 2005, IEEE Transactions on Image Processing.

[12]  Edward Jones,et al.  Accuracy of fish-eye lens models. , 2010, Applied optics.

[13]  Olivier D. Faugeras,et al.  Automatic calibration and removal of distortion from scenes of structured environments , 1995, Optics & Photonics.

[14]  Zhang Wei,et al.  Algorithm of the Delaunay Triangulation Net Interpolated Feature Points for Borehole Data , 2010, 2010 Second International Workshop on Education Technology and Computer Science.

[15]  Sing Bing Kang,et al.  Semi-automatic methods for recovering radial distortion parameters from a single image , 1997 .

[16]  R. Sibson,et al.  A brief description of natural neighbor interpolation , 1981 .

[17]  Shree K. Nayar,et al.  A Theory of Single-Viewpoint Catadioptric Image Formation , 1999, International Journal of Computer Vision.

[18]  Quang-Tuan Luong,et al.  Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices , 1997, International Journal of Computer Vision.

[19]  Roland Siegwart,et al.  A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion , 2006, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06).