Skip to main content

Multi-camera Systems for 3D Video Production

  • Chapter
3D Video and Its Applications
  • 1161 Accesses

Abstract

Drastic advances of digital technologies and the Internet in this decade have made digital (still and video) cameras ubiquitous in everyday life. Moreover, computer vision technologies such as automatic focusing on human faces and image stabilization against hand vibrations have been implemented in modern cameras. This chapter first discusses the design factors of multi-camera systems for 3D video production: camera arrangement, lens and depth-of-focus, shutter speed, lighting, and background. Then three practical studio implementations at Kyoto University are introduced to demonstrate that high fidelity 3D video can be produced with modern off-the-shelf imaging devices. The latter half of the chapter discusses practical geometric and photometric calibration procedures with their quantitative performance evaluation results in the Kyoto University 3D video studios. The imaging devices and their calibration procedures introduced in this chapter can easily be implemented to start research and development of 3D video.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    In what follows, we simply refer video cameras as cameras.

References

  1. Batlle, J., Mouaddib, E., Salvi, J.: Recent progress in coded structured light as a technique to solve the correspondence problem: a survey. Pattern Recognit. 31(7), 963–982 (1998)

    Article  Google Scholar 

  2. Bayer, B.E.: US Patent 3971065: Color imaging array (1976)

    Google Scholar 

  3. Bouguet, J.-Y.: Camera Calibration Toolbox for Matlab. http://www.vision.caltech.edu/bouguetj/calib_doc/

  4. Bradski, G.: The OpenCV Library (2000). http://opencv.willowgarage.com

  5. Virtualizing Engine. Private communication with Profs. Takeo Kanade and Yaser Sheikh, Robotics Institute, Carnegie Mellon University, PA (2011)

    Google Scholar 

  6. Fitzgibbon, A.W., Zisserman, A.: Automatic camera recovery for closed or open image sequences. In: Proc. of European Conference on Computer Vision, pp. 311–326 (1998)

    Google Scholar 

  7. Gevers, T., Stokman, H.M.G., van de Weijer, J.: Colour constancy from hyper-spectral data. In: Proc. of British Machine Vision Conference (2000)

    Google Scholar 

  8. Goldlüecke, B., Magnor, M.: Joint 3D-reconstruction and background separation in multiple views using graph cuts. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 683–688 (2003)

    Google Scholar 

  9. Guillemaut, J.Y., Hilton, A., Starck, J., Kilner, J., Grau, O.: A Bayesian framework for simultaneous matting and 3D reconstruction. In: Proc. of International Conference on 3-D Digital Imaging and Modeling, pp. 167–176 (2007)

    Chapter  Google Scholar 

  10. Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  11. Hernandez, C., Schmitt, F., Cipolla, R.: Silhouette coherence for camera calibration under circular motion. IEEE Trans. Pattern Anal. Mach. Intell. 29(2), 343–349 (2007)

    Article  Google Scholar 

  12. ISO/TR 16066: Standard Object Colour Spectra Database for Colour Reproduction Evaluation (SOCS) (2003)

    Google Scholar 

  13. Ivanov, Y., Bobick, A., Liu, J.: Fast lighting independent background subtraction. Int. J. Comput. Vis. 37(2), 199–207 (2000)

    Article  MATH  Google Scholar 

  14. Kim, S.J., Pollefeys, M.: Robust radiometric calibration and vignetting correction. IEEE Trans. Pattern Anal. Mach. Intell. 30(4), 562–576 (2008)

    Article  Google Scholar 

  15. Levoy, M., Hanrahan, P.: Light field rendering. In: Proc. of ACM SIGGRAPH, pp. 31–42 (1996)

    Google Scholar 

  16. Matsuyama, T., Hiura, S., Wada, T., Murase, K., Toshioka, A.: Dynamic memory: architecture for real time integration of visual perception, camera action, and network communication. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 728–735 (2000)

    Google Scholar 

  17. Matsuyama, T., Ukita, N.: Real-time multitarget tracking by a cooperative distributed vision system. Proc. IEEE 90(7), 1136–1150 (2002)

    Article  Google Scholar 

  18. Miyake, Y., Yokoyama, Y., Tsumura, N., Haneishi, H., Miyata, K., Hayashi, J.: Development of multiband color imaging systems for recordings of art paintings. In: Proc. of SPIE, pp. 218–225 (1998)

    Google Scholar 

  19. Morimoto, T., Mihashi, T., Ikeuchi, K.: Color restoration method based on spectral information using normalized cut. Int. J. Autom. Comput. 5, 226–233 (2008)

    Article  Google Scholar 

  20. Nister, D.: An efficient solution to the five-point relative pose problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 756–770 (2004)

    Article  Google Scholar 

  21. Nobuhara, S., Kimura, Y., Matsuyama, T.: Object-oriented color calibration of multi-viewpoint cameras in sparse and convergent arrangement. IPSJ Trans. Comput. Vis. Appl. 2, 132–144 (2010)

    Google Scholar 

  22. Nobuhara, S., Tsuda, Y., Ohama, I., Matsuyama, T.: Multi-viewpoint silhouette extraction with 3D context-aware error detection, correction, and shadow suppression. IPSJ Trans. Comput. Vis. Appl. 1, 242–259 (2009)

    Google Scholar 

  23. Okutomi, M., Kanade, T.: A multiple-baseline stereo. IEEE Trans. Pattern Anal. Mach. Intell. 15(1), 353–363 (1993)

    Article  Google Scholar 

  24. Pascale, D.: RGB coordinates of the ColorChecker (2006). http://www.babelcolor.com/main_level/ColorChecker.htm

  25. PMDTechnologies GmbH: CamCube3.0 (2010)

    Google Scholar 

  26. Salvi, J., Pagès, J., Batlle, J.: Pattern codification strategies in structured light systems. Pattern Recognit. 37(4), 827–849 (2004)

    Article  MATH  Google Scholar 

  27. Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int. J. Comput. Vis. 47, 7–42 (2002)

    Article  MATH  Google Scholar 

  28. Starck, J., Maki, A., Nobuhara, S., Hilton, A., Matsuyama, T.: The multiple-camera 3-d production studio. IEEE Trans. Circuits Syst. Video Technol. 19(6), 856–869 (2009)

    Article  Google Scholar 

  29. Toyoura, M., Iiyama, M., Kakusho, K., Minoh, M.: Silhouette extraction with random pattern backgrounds for the volume intersection method. In: Proc. of International Conference on 3-D Digital Imaging and Modeling, pp. 225–232 (2007)

    Chapter  Google Scholar 

  30. Wada, T., Matsuyama, T.: Appearance sphere: Background model for pan-tilt-zoom camera. In: Proc. of International Conference on Pattern Recognition, pp. A-718–A-722 (1996)

    Google Scholar 

  31. Yamaguchi, T., Wilburn, B., Ofek, E.: Video-based modeling of dynamic hair. In: Proc. of PSIVT, pp. 585–596 (2009)

    Google Scholar 

  32. Zeng, G., Quan, L.: Silhouette extraction from multiple images of an unknown background. In: Proc. of Asian Conference on Computer Vision, pp. 628–633 (2004)

    Google Scholar 

  33. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  34. Zheng, Y., Yu, J., Kang, S., Lin, S., Kambhamettu, C.: Single-image vignetting correction using radial gradient symmetry. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag London

About this chapter

Cite this chapter

Matsuyama, T., Nobuhara, S., Takai, T., Tung, T. (2012). Multi-camera Systems for 3D Video Production. In: 3D Video and Its Applications. Springer, London. https://doi.org/10.1007/978-1-4471-4120-4_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-4120-4_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4119-8

  • Online ISBN: 978-1-4471-4120-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics