Capturing mosaic-based panoramic depth images with a single standard camera

In this paper we present a panoramic depth imaging system. The system is mosaic-based which means that we use a single rotating camera and assemble the captured images in a mosaic. Due to a setoff of the camera’s optical center from the rotational center of the system we are able to capture the motion parallax effect which enables the stereo reconstruction. The camera is rotating on a circular path with the step defined by an angle equivalent to one column of the captured image. The equation for depth estimation can be easily extracted from system geometry. To find the corresponding points on a stereo pair of panoramic images the epipolar geometry needs to be determined. It can be shown that the epipolar geometry is very simple if we are doing the reconstruction based on a symmetric pair of stereo panoramic images. We get a symmetric pair of stereo panoramic images when we take symmetric columns on the left and on the right side from the captured image center column. Epipolar lines of the symmetrical pair of panoramic images are image rows. We focused mainly on the system analysis. The system performs well in the reconstruction of small indoor spaces.

[1]  Shmuel Peleg,et al.  Mosaicing on Adaptive Manifolds , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

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

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

[4]  Anup Basu,et al.  Alternative models for fish-eye lenses , 1995, Pattern Recognit. Lett..

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

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

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

[8]  Franc Solina,et al.  User interface for video observation over the internet , 1998, J. Netw. Comput. Appl..

[9]  Tomas Pajdla,et al.  Panoramic cameras for 3D computation , 2000 .

[10]  Shree K. Nayar,et al.  360/spl times/360 mosaics , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[11]  Richard Szeliski,et al.  Creating full view panoramic image mosaics and texture-mapped models , 1997, International Conference on Computer Graphics and Interactive Techniques.

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

[13]  S. P. Mudur,et al.  Three-dimensional computer vision: a geometric viewpoint , 1993 .

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

[15]  Shree K. Nayar,et al.  Folded catadioptric cameras , 1999, CVPR 1999.

[16]  Wolfgang Pölzleitner,et al.  Robust disparity estimation in terrain modeling for spacecraft navigation , 1992, [1992] Proceedings. 11th IAPR International Conference on Pattern Recognition.

[17]  Rajiv Gupta,et al.  Linear Pushbroom Cameras , 1994, ECCV.

[18]  Reinhard Klette,et al.  Geometrical Fundamentals of Polycentric Panoramas , 2001, ICCV.

[19]  Paul Rademacher,et al.  Multiple-center-of-projection images , 1998, SIGGRAPH.

[20]  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).

[21]  Ryad Benosman,et al.  Panoramic stereovision sensor , 1998 .

[22]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .