Robust Dynamic 3D Shape Measurement with Hybrid Fourier-Transform Phase-Shifting Profilometry

  • Jiaming Qian
  • Tianyang Tao
  • Shijie Feng
  • Qian Chen
  • Chao ZuoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11903)


In this work, we propose a novel hybrid Fourier-transform phase-shifting profilometry method to integrate the advantages of Fourier-transform profilometry (FTP) and phase-shifting profilometry (PSP). The motion vulnerability of multi-shot PSP can be significantly alleviated through the combination of single-shot FTP, while the high accuracy of PSP can also be preserved when the object is motionless. We design a phase-based pixel-wise motion detection strategy that can accurately outline the moving object regions from their motionless counterparts. The final measurement result is obtained by fusing the determined regions where the PSP or FTP is applied correspondingly. To validate the proposed hybrid approach, we develop a real-time 3D shape measurement system for measuring multiple isolated moving objects. Experimental results demonstrate that our method achieves significantly higher precision and better robustness compared with conventional approaches where PSP or FTP is applied separately.


Fourier-transform profilometry Phase-shifting profilometry Motion detection 



National Natural Science Fund of China (61722506, 61705105, 111574152); National Key R&D Program of China (2017YFF0106403); Final Assembly ‘13th Five-Year Plan’ Advanced Research Project of China (30102070102); Equipment Advanced Research Fund of China (61404150202), The Key Research and Development Program of Jiangsu Province, China (BE2017162); Outstanding Youth Foundation of Jiangsu Province of China (BK20170034); National Defense Science and Technology Foundation of China (0106173); ‘Six Talent Peaks’ project of Jiangsu Province, China (2015-DZXX-009); ‘333 Engineering’ research project of Jiangsu Province, China (BRA2016407, BRA2015294); Fundamental Research Funds for the Central Universities (30917011204, 30916011322); Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense (3091601410414); China Postdoctoral Science Foundation (2017M621747), and Jiangsu Planned Projects for Postdoctoral Research Funds (1701038A).


  1. 1.
    Geng, J.: Structured-light 3D surface imaging: a tutorial. Adv. Opt. Photonics 3, 128–160 (2011)CrossRefGoogle Scholar
  2. 2.
    Gorthi, S.S., Rastogi, P.: Fringe projection techniques: whither we are? Opt. Lasers Eng. 48, 133–140 (2010)CrossRefGoogle Scholar
  3. 3.
    Zhang, S.: Recent progresses on real-time 3D shape measurement using digital fringe projection techniques. Opt. Lasers Eng. 48, 149–158 (2010)CrossRefGoogle Scholar
  4. 4.
    Zuo, C., Feng, S., Huang, L., Tao, T., Yin, W., Chen, Q.: Phase shifting algorithms for fringe projection profilometry: a review. Opt. Lasers Eng. 109, 23–59 (2018)CrossRefGoogle Scholar
  5. 5.
    Srinivasan, V., Liu, H.-C., Halioua, M.: Automated phase-measuring profilometry of 3-D diuse objects. Appl. Optics 23, 3105–3108 (1984)CrossRefGoogle Scholar
  6. 6.
    Su, X., Zhang, Q.: Dynamic 3-D shape measurement method: a review. Opt. Lasers Eng. 48, 191–204 (2010)CrossRefGoogle Scholar
  7. 7.
    Takeda, M., Ina, H., Kobayashi, S.: Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry. JosA 72, 156–160 (1982)CrossRefGoogle Scholar
  8. 8.
    Li, J., Su, X., Guo, L.: Improved fourier transform profilometry for the automatic measurement of three-dimensional object shapes. Opt. Eng. 29, 1439–1445 (1990)CrossRefGoogle Scholar
  9. 9.
    Guo, H., Huang, P.S.: 3-D shape measurement by use of a modified fourier transform method. In: Proceedings of SPIE -International Society for Optical Engineering, vol. 7066 (2008)Google Scholar
  10. 10.
    Zuo, C., Tao, T., Feng, S., Huang, L., Asundi, A., Chen, Q.: Micro fourier transform profilometry (FTP): 3D shape measurement at 10,000 frames per second. Opt. Lasers Eng. 102, 70–91 (2018)CrossRefGoogle Scholar
  11. 11.
    Li, J., Hassebrook, L.G., Guan, C.: Optimized two-frequency phase-measuring-profilometry light-sensor temporal-noise sensitivity. JOSA A 20, 106–115 (2003)CrossRefGoogle Scholar
  12. 12.
    Su, X.-Y., Von Bally, G., Vukicevic, D.: Phase-stepping grating profilometry: utilization of intensity modulation analysis in complex objects evaluation. Opt. Commun. 98, 141–150 (1993)CrossRefGoogle Scholar
  13. 13.
    Zhang, S., Van Der Weide, D., Oliver, J.: Superfast phase-shifting method for 3-D shape measurement. Opt. Express 18, 9684–9689 (2010)CrossRefGoogle Scholar
  14. 14.
    Zuo, C., Huang, L., Zhang, M., Chen, Q., Asundi, A.: Temporal phase unwrapping algorithms for fringe projection profilometry: a comparative review. Opt. Lasers Eng. 85, 84–103 (2016)CrossRefGoogle Scholar
  15. 15.
    Zhang, Z., Towers, C.E., Towers, D.P.: Time eÿcient color fringe projection system for 3D shape and color using optimum 3-frequency selection. Opt. Express 14, 6444–6455 (2006)CrossRefGoogle Scholar
  16. 16.
    Bräuer-Burchardt, C., Munkelt, C., Heinze, M., Kühmstedt, P., Notni, G.: Using geometric constraints to solve the point correspondence problem in fringe projection based 3D measuring systems. In: Maino, G., Foresti, G.L. (eds.) ICIAP 2011. LNCS, vol. 6979, pp. 265–274. Springer, Heidelberg (2011). Scholar
  17. 17.
    Weise, T., Leibe, B., Van Gool, L.: Fast 3D scanning with automatic motion compensation. In: IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2007, pp. 1–8. IEEE (2007)Google Scholar
  18. 18.
    Tao, T., et al.: High-speed real-time 3D shape measurement based on adaptive depth constraint. Opt. Express 26, 22440–22456 (2018)CrossRefGoogle Scholar
  19. 19.
    Tao, T., Chen, Q., Feng, S., Hu, Y., Zhang, M., Zuo, C.: High-precision real-time 3D shape measurement based on a quad-camera system. J. Opt. 20, 014009 (2017)CrossRefGoogle Scholar
  20. 20.
    Lu, L., Xi, J., Yu, Y., Guo, Q.: Improving the accuracy performance of phase-shifting profilometry for the measurement of objects in motion. Opt. Lett. 39, 6715–6718 (2014)CrossRefGoogle Scholar
  21. 21.
    Feng, S., et al.: Robust dynamic 3-D measurements with motion-compensated phase-shifting profilometry. Opt. Lasers Eng. 103, 127–138 (2018)CrossRefGoogle Scholar
  22. 22.
    Li, B., Liu, Z., Zhang, S.: Motion-induced error reduction by combining fourier transform profilometry with phase-shifting profilometry. Opt. Express 24, 23289–23303 (2016)CrossRefGoogle Scholar
  23. 23.
    Cong, P., Xiong, Z., Zhang, Y., Zhao, S., Wu, F.: Accurate dynamic 3D sensing with fourier-assisted phase shifting. IEEE J. Sel. Top. Signal Process. 9, 396–408 (2015)CrossRefGoogle Scholar
  24. 24.
    Liu, Z., Zibley, P.C., Zhang, S.: Motion-induced error compensation for phase shifting profilometry. Opt. Express 26, 12632–12637 (2018)CrossRefGoogle Scholar
  25. 25.
    Yang, Z., Xiong, Z., Zhang, Y., Wang, J., Wu, F.: Depth acquisition from density modulated binary patterns. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 25–32 (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jiaming Qian
    • 1
    • 2
    • 3
  • Tianyang Tao
    • 1
    • 2
    • 3
  • Shijie Feng
    • 1
    • 2
    • 3
  • Qian Chen
    • 1
    • 2
  • Chao Zuo
    • 1
    • 2
    • 3
    Email author
  1. 1.School of Electronic and Optical Engineering, Nanjing University of Science and TechnologyNanjingChina
  2. 2.Jiangsu Key Laboratory of Spectral Imaging and Intelligent SenseNanjing University of Science and TechnologyNanjingChina
  3. 3.Smart Computational Imaging (SCI) LaboratoryNanjing University of Science and TechnologyNanjingChina

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