Dynamic 3D Scanning Based on Optical Tracking | SpringerLink
Skip to main content

Dynamic 3D Scanning Based on Optical Tracking

  • Conference paper
  • First Online:
Entertainment Computing – ICEC 2020 (ICEC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12523))

Included in the following conference series:

  • 1329 Accesses

Abstract

In order to solve the problem that traditional binocular vision 3D scanning requires multiple scans and then registration, a dynamic 3D scanning method based on optical tracking is proposed. The first part is monocular optical scanning, which uses laser stripes as the active light source to achieve the function of 3D scanning. The second part is monocular optical tracking, which realizes the calculation and tracking of the position and posture of the scanning device, and instantly converts the point cloud data obtained by the scanning camera to the tracking camera coordinate system, realizing real-time data registration during the dynamic scanning process. The experimental results show that this method can achieve dynamic scanning to obtain the point cloud information of the object. The accuracy of the scan is about 1 mm in the direction of the \({\mathbf{XOY}}\) coordinate plane of the coordinate system and about 0.08 mm in the direction of the z-axis. At the same time, the scanning time can be saved by 50% compared with the traditional binocular vision 3D scanning method.

Supported by “the Fundamental Research Funds for the Central Universities”, and “National Natural Science Foundation of China, No.61702422”.

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

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 11439
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 14299
Price includes VAT (Japan)
  • Compact, lightweight 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

Similar content being viewed by others

References

  1. Bloesch, M., Czarnowski, J., Clark, R., Leutenegger, S., Davison, A.J.: Codeslam - learning a compact, optimisable representation for dense visual slam. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2560–2568 (2018)

    Google Scholar 

  2. Davison: Real-time simultaneous localisation and mapping with a single camera. In: Proceedings Ninth IEEE International Conference on Computer Vision, vol. 2, pp. 1403–1410 (2003)

    Google Scholar 

  3. Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: Monoslam: real-time single camera slam. IEEE Trans. Pattern Anal. Mach. Intell. 29(6), 1052–1067 (2007)

    Article  Google Scholar 

  4. Jiang, J., Zeng, L., Chen, B., Lu, Y., Xiong, W.: An accurate and flexible technique for camera calibration. Computing 101(4), 1–18 (2019)

    MathSciNet  Google Scholar 

  5. Tsai, R.: An efficient and accurate camera calibration technique for 3D machine vision. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 364–374 (1986)

    Google Scholar 

  6. Tang, Q.H., Zhang, Z.Y.: Camera self-calibration based on multiple view images. Computer Engineering and Science (2017)

    Google Scholar 

  7. Tsai, R.: A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf tv cameras and lenses. IEEE J. Robot. Autom. 3(4), 323–344 (1987)

    Article  Google Scholar 

  8. Xin, S., Nousias, S., Kutulakos, K.N., Sankaranarayanan, A.C., Narasimhan, S.G., Gkioulekas, I.: A theory of fermat paths for non-line-of-sight shape reconstruction. In: Proceedings of (CVPR) Computer Vision and Pattern Recognition (June 2019)

    Google Scholar 

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

    Article  Google Scholar 

  10. Zhang, Z., Yuan, L.: Building a 3D scanner system based on monocular vision. Appl. Opt. 51(11), 1638 (2012)

    Article  Google Scholar 

  11. Zhengyou, Z.: Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of the Seventh IEEE International Conference on Computer Vision, vol. 1, pp. 666–673 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhang Zhiyi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jiangtao, H., Longxing, Y., Long, Y., Zhiyi, Z. (2020). Dynamic 3D Scanning Based on Optical Tracking. In: Nunes, N.J., Ma, L., Wang, M., Correia, N., Pan, Z. (eds) Entertainment Computing – ICEC 2020. ICEC 2020. Lecture Notes in Computer Science(), vol 12523. Springer, Cham. https://doi.org/10.1007/978-3-030-65736-9_39

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-65736-9_39

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65735-2

  • Online ISBN: 978-3-030-65736-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics