Fast panoramic stereo matching using cylindrical maximum surfaces

This paper presents a fast panoramic stereo matching algorithm using a cylindrical maximum surface technique. The disparity for a pair of panoramic images is found in a cylindrical shaped correlation coefficient volume by obtaining the maximum surface rather than simply choosing a position that gives the maximum correlation coefficient value. The use of our cylindrical maximum surface technique ensures that the disparities obtained at the left and the right columns of the panoramic stereo images are properly constrained. Typical running time for a pair of 1324 /spl times/ 120 images is about 0.33 s on a 1.7-GHz PC. A variety of real images have been tested, and good results have been obtained.

[1]  Bruno Schneuwly,et al.  Dynamic workspace monitoring , 1994, Other Conferences.

[2]  Ingemar J. Cox,et al.  A maximum-flow formulation of the N-camera stereo correspondence problem , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[3]  Hynek Bakstein,et al.  Omnivergent Stereo-panoramas with a Fish-eye Lens , 2001 .

[4]  Aaron F. Bobick,et al.  Large Occlusion Stereo , 1999, International Journal of Computer Vision.

[5]  Jake K. Aggarwal,et al.  Structure from stereo-a review , 1989, IEEE Trans. Syst. Man Cybern..

[6]  Changming Sun,et al.  Circular shortest path in images , 2003, Pattern Recognit..

[7]  Anup Basu,et al.  Panoramic stereo reconstruction using non-SVP optics , 2002, Object recognition supported by user interaction for service robots.

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

[9]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[10]  Dan Xu,et al.  Complex wavelet-based image mosaics using edge-preserving visual perception modeling , 1999, Comput. Graph..

[11]  Yael Pritch,et al.  Cameras for stereo panoramic imaging , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[12]  Laurent Moll,et al.  Real time correlation-based stereo: algorithm, implementations and applications , 1993 .

[13]  Alan L. Yuille,et al.  Multilevel Enhancement and Detection of Stereo Disparity Surfaces , 1995, Artif. Intell..

[14]  Chi-Keung Tang,et al.  Efficient Dense Depth Estimation from Dense Multiperspective Panoramas , 2001, ICCV.

[15]  Changming Sun,et al.  Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-Surface Techniques , 2002, International Journal of Computer Vision.

[16]  Richard Szeliski,et al.  Stereo reconstruction from multiperspective panoramas , 2004 .

[17]  Yael Pritch,et al.  Omnistereo: Panoramic Stereo Imaging , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Georgy L. Gimel'farb,et al.  Experiments with symmetrized intensity‐based dynamic programming algorithms for reconstructing digital terrain model , 1992, Int. J. Imaging Syst. Technol..

[19]  David Salesin,et al.  Multiperspective panoramas for cel animation , 1997, SIGGRAPH.

[20]  Changming Sun A Fast Stereo Matching Method , 1997 .

[21]  Qian Chen,et al.  Building human face models from two images , 1998, 1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175).

[22]  P. Debevec,et al.  Image-based modeling, rendering, and lighting , 2002, IEEE Computer Graphics and Applications.

[23]  Soon Ki Jung,et al.  Constructing cylindrical panoramic image using equidistant matching , 1999 .

[24]  Yasushi Yagi,et al.  Guidance of a Mobile Robot with Environmental Map Using Omnidirectional Image Sensor COPIS (Special Issue on Image Processing and Understanding) , 1993 .

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

[26]  Shree K. Nayar,et al.  Real-Time Omnidirectional and Panoramic Stereo , 1998 .

[27]  Changming Sun,et al.  Circular shortest paths by branch and bound , 2003, Pattern Recognit..

[28]  Saburo Tsuji,et al.  Panoramic representation for route recognition by a mobile robot , 1992, International Journal of Computer Vision.

[29]  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.

[30]  K. Sunil Kumar,et al.  New algorithms for 3D surface description from binocular stereo using integration , 1994 .

[31]  Shmuel Peleg,et al.  Stereo panorama with a single camera , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).