Characterization of errors in compositing panoramic images

In this paper we describe the effect of errors in the intrinsic camera parameters on reconstructed panoramic images. A panoramic image is created by first capturing a sequence of images while rotating the camera about a vertical axis a full 360/spl deg/. The subsequent steps are projecting the original rectilinear images onto cylindrical surfaces and compositing them to form the panoramic image. Our analysis has led to a technique that allows simultaneous recovery of the camera focal length and properly composited panoramic images. The correct focal length can be determined by iterating the processes of projecting the original rectilinear images onto cylindrical surfaces given an estimate of the focal length and compositing the resulting images to yield an increasingly better estimate of the focal length. This paper shows that the convergence towards the correct focal length is exponential.

[1]  Hiroshi Ishiguro,et al.  Omni-Directional Stereo , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  D. W. Murray,et al.  Camera Calibration using Vanishing Points , 1992 .

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

[4]  Duane C. Brown,et al.  Close-Range Camera Calibration , 1971 .

[5]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[6]  Richard Szeliski,et al.  Image mosaicing for tele-reality applications , 1994, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision.

[7]  Leonard McMillan,et al.  Plenoptic Modeling: An Image-Based Rendering System , 2023 .

[8]  Richard Szeliski,et al.  Video mosaics for virtual environments , 1996, IEEE Computer Graphics and Applications.

[9]  Soren W. Henriksen,et al.  Manual of photogrammetry , 1980 .

[10]  Gideon P. Stein.  Accurate internal camera calibration using rotation, with analysis of sources of error , 1995, Proceedings of IEEE International Conference on Computer Vision.

[11]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[12]  Harry Shum,et al.  Construction and refinement of panoramic mosaics with global and local alignment , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[13]  Richard I. Hartley.  Self-Calibration from Multiple Views with a Rotating Camera , 1994, ECCV.

[14]  L. Dron.  Dynamic camera self-calibration from controlled motion sequences , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Lawrence S. Kroll.  Mathematica--A System for Doing Mathematics by Computer. , 1989 .

[16]  Richard Szeliski,et al.  Recovering 3D Shape and Motion from Image Streams Using Nonlinear Least Squares , 1994, J. Vis. Commun. Image Represent..

[17]  Carlo Tomasi,et al.  Comparison of approaches to egomotion computation , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Sing Bing Kang,et al.  Survey of image-based rendering techniques , 1998, Electronic Imaging.

[19]  Sing Bing Kang,et al.  Characterization of Errors in Compositing Panoramic Images , 1999, Comput. Vis. Image Underst..

[20]  Richard Szeliski,et al.  Extraction of Concise and Realistic 3-D Models from Real Data , 1995 .

[21]  Michael A. Penna.  Camera Calibration: A Quick and Easy Way to Determine the Scale Factor , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[23]  Richard I. Hartley,et al.  An algorithm for self calibration from several views , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[24]  Richard Szeliski,et al.  Creating full view panoramic image mosaics and environment maps , 1997, SIGGRAPH.

[25]  Shenchang Eric Chen,et al.  QuickTime VR: an image-based approach to virtual environment navigation , 1995, SIGGRAPH.

[26]  Richard Szeliski,et al.  3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[27]  Wen-Hsiang Tsai,et al.  Camera Calibration by Vanishing Lines for 3-D Computer Vision , 1991, IEEE Trans. Pattern Anal. Mach. Intell..