article

Omnivergent Stereo

Authors:

Steven M. Seitz,

Heung-Yeung ShumAuthors Info & Claims

International Journal of Computer Vision, Volume 48, Issue 3

Pages 159 - 172

https://doi.org/10.1023/A:1016342731674

Published: 21 July 2002 Publication History

Abstract

The notion of a virtual camera for optimal 3D reconstruction is introduced. Instead of planar perspective images that collect many rays at a fixed viewpoint, omnivergent cameras collect a small number of rays at many different viewpoints. The resulting 2D manifold of rays is arranged into two multiple-perspective images for stereo reconstruction. We call such images omnivergent images, and the process of reconstructing the scene from such images omnivergent stereo. This procedure is shown to produce 3D scene models with minimal reconstruction error, due to the fact that for any point in the 3D scene, two rays with maximum vergence angle can be found in the omnivergent images. Furthermore, omnivergent images are shown to have horizontal epipolar lines, enabling the application of traditional stereo matching algorithms, without modification. Three types of omnivergent virtual cameras are presented: spherical omnivergent cameras, center-strip cameras and dual-strip cameras.

References

[1]

Baker, S. and Nayar, S. 1998. A theory of catadioptric image formation. In Proc. Sixth Int. Conf. on Computer Vision, pp. 35-42.

Digital Library

[2]

Bolles, R.C., Baker, H.H., and Marimont, D.H. 1987. Epipolar-plane image analysis: An approach to determining structure from motion. Int. J. of Computer Vision, 1(1):7-55.

[3]

Chen, S.E. 1995. Quicktime VR--An image-based approach to virtual environment navigation. In Proc. SIGGRAPH 95, pp. 29- 38.

Digital Library

[4]

Gortler, S.J., Grzeszczuk, R., Szeliski, R., and Cohen, M.F. 1996. The lumigraph. In Proc. SIGGRAPH 96, pp. 43-54.

Digital Library

[5]

Huang, H.C. and Hung, Y.P. 1998. Panoramic stereo imaging system with automatic disparity warping and seaming. Graphical Models and Image Processing, 60(3): 196-208.

Digital Library

[6]

Ishiguro, H., Yamamoto, M., and Tsuji, S. 1992. Omni-directional stereo. PAMI, 14:257-262.

Digital Library

[7]

Kang, S.B. and Szeliski, R. 1996. 3-D scene data recovery using omnidirectional multibaseline stereo. In Proc. Computer Vision and Pattern Recognition Conf., pp. 364-370.

Digital Library

[8]

Katayama, A., Tanaka, K., Oshino, T., and Tamura, H. 1995. A viewpoint dependent stereoscopic display using interpolation of multi-viewpoint images. In Proc. SPIE, vol. 2409A, pp. 21-30.

[9]

Kumar, R., Anandan, P., Irani, M., Bergen, J., and Hanna, K. 1995. Representation of scenes from collections of images. In Proc. IEEE Workshop on Representation of Visual Scenes, pp. 10-17.

Digital Library

[10]

Levoy, M. and Hanrahan, P. 1996. Light field rendering. In Proc. SIGGRAPH 96.

Digital Library

[11]

Mann, S. and Picard, R. 1994. Virtual bellows: Constructing high-quality images from video. In Proc. First Int. Conf. on Image Processing.

[12]

McMillan, L. and Bishop, G. 1995. Plenoptic modeling: An image-based rendering system. In Proc. SIGGRAPH 95, pp. 39-46.

Digital Library

[13]

Nayar, S.K. and Karmarkar, A. 2000. 360 × 360 mosaics. In Proc. Computer Vision and Pattern Recognition Conf., pp. 388-395.

[14]

Okutomi, M. and Kanade, T. 1985. A multiple-baseline stereo. IEEE Trans. on Pattern Analysis and Machine Intelligence, 15 (4):353- 363.

Digital Library

[15]

Pajdla, T. 2001. Epipolar geometry of some non-classical cameras. In Proceedings of Computer Vision Winter Workshop, Slovenian Pattern Recognition Society, pp. 223-233.

[16]

Peleg, S. and Ben-Ezra, M. 1999. Stereo panorama with a single camera. In Proc. Computer Vision and Pattern Recognition Conf., pp. 395-401.

[17]

Peleg, S. and Herman, J. 1997. Panoramic mosaics by manifold projection. In Proc. Computer Vision and Pattern Recognition Conf., pp. 338-343.

Digital Library

[18]

Peleg, S., Pritch, Y., and Ben-Ezra, M. 2000. Cameras for stereo panoramic imaging. In Proc. Computer Vision and Pattern Recognition Conf., pp. 208-214.

[19]

Seitz, S.M. 2001. The space of all stereo images. In Proc. Eighth Int. Conf. on Computer Vision, pp. 26-33.

[20]

Shum, H.-Y., Kalai, A., and Seitz, S.M. 1999. Omnivergent stereo. In Proc. Seventh Int. Conf. on Computer Vision, pp. 22- 29.

[21]

Shum, H.-Y. and Szeliski, R. 1999. Stereo reconstruction from multiperspective panoramas. In Proc. Seventh Int. Conf. on Computer Vision, pp. 14-21.

[22]

Szeliski, R. 1996. Video mosaics for virtual environments. IEEE Computer Graphics and Applications, 16(2):22-30.

Digital Library

[23]

Wood, D.N., Finkelstein, A., Hughes, J.F., Thayer, C.E., and Salesin, D.H. 1997. Multiperspective panoramas for cel animation. In Proc. SIGGRAPH 97, pp. 243-250.

Digital Library

Cited By

Couture VLanger MRoy S(2012)Perception of blending in stereo motion panoramasACM Transactions on Applied Perception10.1145/2325722.23257289:3(1-10)Online publication date: 2-Aug-2012
https://dl.acm.org/doi/10.1145/2325722.2325728
Sturm PRamalingam STardif JGasparini SBarreto J(2011)Camera Models and Fundamental Concepts Used in Geometric Computer VisionFoundations and Trends® in Computer Graphics and Vision10.1561/06000000236:1–2(1-183)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.1561/0600000023

Index Terms

Omnivergent Stereo
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

Recommendations

Minimal Aspect Distortion (MAD) Mosaicing of Long Scenes

Long scenes can be imaged by mosaicing multiple images from cameras scanning the scene. We address the case of a video camera scanning a scene while moving in a long path, e.g. scanning a city street from a driving car, or scanning a terrain from a low ...
On the Importance of Being Asymmetric in Stereopsis—Or Why We Should Use Skewed Parallel Cameras

This paper presents a new clever camera sensor, where relative pose determination is not needed, and the sensor is simultaneously capable of using vergence micromovements. Sweeping depth using vergence micromovements promises subpixel depth precision, ...
Stereo Reconstruction from Multiperspective Panoramas

Abstract--A new approach to computing a panoramic (360 degrees) depth map is presented in this paper. Our approach uses a large collection of images taken by a camera whose motion has been constrained to planar concentric circles. We resample regular ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

Copyright © Copyright © 2002 Kluwer Academic Publishers.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 21 July 2002

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 28 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Couture VLanger MRoy S(2012)Perception of blending in stereo motion panoramasACM Transactions on Applied Perception10.1145/2325722.23257289:3(1-10)Online publication date: 2-Aug-2012
https://dl.acm.org/doi/10.1145/2325722.2325728
Sturm PRamalingam STardif JGasparini SBarreto J(2011)Camera Models and Fundamental Concepts Used in Geometric Computer VisionFoundations and Trends® in Computer Graphics and Vision10.1561/06000000236:1–2(1-183)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.1561/0600000023

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents