Skip to main content

Estimation Value for Three Dimension Reconstruction

  • Conference paper
  • First Online:
Multimedia and Ubiquitous Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 240))

  • 1176 Accesses

Abstract

This paper deals with a fundamental problem for 3D model acquisition after camera calibration [1]. We present an approach to estimate a robust fundamental matrix for camera calibration [2, 3]. Single axis motion can be described in terms of its fixed entities, those geometric objects in space or in the image that remain invariant throughout the sequence. In particular, corresponding epipolar lines between two images intersect at the image of the rotation axis. This constraint is then used to remove the outliers and provides new algorithms for the computing the fundamental matrix. In the simulation results, our method can be used to compute the fundamental matrix for camera calibration more efficiently.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
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

References

  1. Jang G, Tusi HT, Quan L, Zisserman A (2003) Single axis geometry by fitting conics. IEEE Trans Pattern Anal Mach Intell 25(10):1343–1348

    Google Scholar 

  2. Zhang Z (1998) Determining the epipolar geometry and its uncertainty: a review. Int J Comput Vis 27(2):161–195

    Google Scholar 

  3. Serra J (1982) Image analysis and mathematical morphology, vol 1. Academic Press, New York

    Google Scholar 

  4. Canny J (1986) A computation approach to edge detection. IEEE Trans PAMI 8(6):679–698

    Google Scholar 

  5. Rao K (1993) Extracting salient contours for target recognition: algorithm and performance evaluation. Opt Eng 32(11):2690–2697

    Google Scholar 

  6. Hartly R, Zisserman A (2000) Multiple view geometry in computer vision. Oxford university press, Oxford

    Google Scholar 

Download references

Acknowledgments

Funding of this paper was provided by Namseoul University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tae-Eun Kim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht(Outside the USA)

About this paper

Cite this paper

Kim, TE. (2013). Estimation Value for Three Dimension Reconstruction. In: Park, J., Ng, JY., Jeong, HY., Waluyo, B. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6738-6_118

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-6738-6_118

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6737-9

  • Online ISBN: 978-94-007-6738-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics