3D Structured Light Scanner on the Smartphone

  • Tomislav Pribanić
  • Tomislav Petković
  • Matea ĐonlićEmail author
  • Vincent Angladon
  • Simone Gasparini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9730)


In the recent years turning smartphones into 3D reconstruction devices has been greatly investigated. Different 3D reconstruction concepts have been proposed, and one of the most popular is based on IR projection of a pseudorandom dots (speckle) pattern. We demonstrate our idea how a pseudorandom dots pattern can be used and we also present an active approach applying a structured light (SL) scanning on the smartphone. SL has a number of advantages compared to other 3D reconstruction concepts and likewise our smartphone implementation inherits the same advantages compared to other smartphone based solutions. The shown qualitative and quantitative results demonstrate the comparable outcome with the standard type SL scanner.


Smartphone 3D reconstruction Structured light Pseudorandom dots pattern 



This work has been supported in parts by the Croatian Science Foundation’s funding of the project IP-11-2013-3717. We also acknowledge the support of Croatian-French Program “Cogito”, Hubert Curien partnership, funding the project “Three-dimensional reconstruction using smartphone”.


  1. 1.
    123D Catch. Accessed Nov 2015
  2. 2.
    Trnio. Accessed Nov 2015
  3. 3.
    Tanskanen, P., Kolev, K., Meier, L., Camposeco, F., Saurer, O., Pollefeys, M.: Live metric 3D reconstruction on mobile phones. In: IEEE ICCV 2013, pp. 65–72 (2013)Google Scholar
  4. 4.
    Hartl, A., Gruber, L., Arth, C., Hauswiesner, S., Schmalstieg, D.: Rapid reconstruction of small objects on mobile phones. In: IEEE Conference on CVPR Workshops 2011, pp. 20–27 (2011)Google Scholar
  5. 5.
    Wang, C., Bao, M., Shen, T.: 3D model reconstruction algorithm and implementation based on the mobile device. J. Theor. Appl. Inf. Technol. 46(1), 255–262 (2012)Google Scholar
  6. 6.
    Trimensional. Accessed Nov 2015
  7. 7.
    Won, J.H., Lee, M.H., Park, I.K.: Active 3D shape acquisition using smartphones. In: IEEE Conference on CVPR Workshops 2012, pp. 29–34 (2012)Google Scholar
  8. 8.
  9. 9.
    Slossberg, R., Wetzler, A., Kimmel, R.: Freehand laser scanning using mobile phone. In: Proceeding of the British Machine Vision Conference, pp. 88.1–88.10 (2015)Google Scholar
  10. 10.
    Salvi, J., Fernandez, S., Pribanić, T., LLado, X.: A state of the art in structured light patterns for surface profilometry. Pattern Recogn. 43, 2666–2680 (2010)CrossRefzbMATHGoogle Scholar
  11. 11.
    List of projector phones. Accessed Nov 2015
  12. 12.
  13. 13.
    Reshetouski, I., Ihrke, I.: Mirrors in computer graphics, computer vision and time-of-flight imaging. In: Grzegorzek, M., Theobalt, C., Koch, R., Kolb, A. (eds.) Time-of-Flight and Depth Imaging. LNCS, vol. 8200, pp. 77–104. Springer, Heidelberg (2013)Google Scholar
  14. 14.
    Pribanić, T., Mrvoš, S., Salvi, J.: Efficient multiple phase shift patterns for dense 3D acquisition in structured light scanning. Image Vis. Comput. 28, 1255–1266 (2010)CrossRefGoogle Scholar
  15. 15.
    Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. PAMI 22(11), 1330–1334 (2000)CrossRefGoogle Scholar
  16. 16.
    McIlroy, P., Izadi, S., Fitzgibbon, A.: Kinectrack: Agile 6-DoF tracking using a projected dot pattern. In: International Symposium on Mixed and Augmented Reality, pp. 23–29 (2012)Google Scholar
  17. 17.
    Ishii, I., Yamamoto, K., Doi, K., Tsuji, T.: High-speed 3D image acquisition using coded structured light projection. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 925–930 (2007)Google Scholar
  18. 18.
    Zhang, Y., Xiong, Z., Yang, Z., Wu, F.: Real-time scalable depth sensing with hybrid structured light illumination. IEEE Trans. Image Process. 23, 97–109 (2014)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Petković, T., Pribanić, T., Đonlić, M.: The self-equalizing De Bruijn sequence for 3D profilometry. In: Proceeding of the British Machine Vision Conference, pp. 155.1–155.11 (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Tomislav Pribanić
    • 1
  • Tomislav Petković
    • 1
  • Matea Đonlić
    • 1
    Email author
  • Vincent Angladon
    • 2
  • Simone Gasparini
    • 2
  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia
  2. 2.University of Toulouse, IRIT-INPToulouseFrance

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