Vision-based hybrid 6-DOF displacement estimation for precast concrete member assembly

  • Received : 2017.03.21
  • Accepted : 2017.09.10
  • Published : 2017.10.25


Precast concrete (PC) members are currently being employed for general construction or partial replacement to reduce construction period. As assembly work in PC construction requires connecting PC members accurately, measuring the 6-DOF (degree of freedom) relative displacement is essential. Multiple planar markers and camera-based displacement measurement systems can monitor the 6-DOF relative displacement of PC members. Conventional methods, such as direct linear transformation (DLT) for homography estimation, which are applied to calculate the 6-DOF relative displacement between the camera and marker, have several major problems. One of the problems is that when the marker is partially hidden, the DLT method cannot be applied to calculate the 6-DOF relative displacement. In addition, when the images of markers are blurred, error increases with the DLT method which is employed for its estimation. To solve these problems, a hybrid method, which combines the advantages of the DLT and MCL (Monte Carlo localization) methods, is proposed. The method evaluates the 6-DOF relative displacement more accurately compared to when either the DLT or MCL is used alone. Each subsystem captures an image of a marker and extracts its subpixel coordinates, and then the data are transferred to a main system via a wireless communication network. In the main system, the data from each subsystem are used for 3D visualization. Thereafter, the real-time movements of the PC members are displayed on a tablet PC. To prove the feasibility, the hybrid method is compared with the DLT method and MCL in real experiments.


Supported by : Ministry of Land, Infrastructure and Transport (MOLIT), Ministry of Trade, Industry & Energy (MOTIE)


  1. Abdel, A.Y. and Karara, H. (1971), Direct Linear Transformation from Comparator Coordinates into Object, American Society of Photogrammetry, Washington, D.C., USA.
  2. Caltrans (2004), Slab replacement guidelines, State of California Department of Transportation, Sacramento, CA, USA.
  3. Coppelia Robotics (2016), V-REP
  4. Edwin O. (2011), "AprilTag: A robust and flexible visual fiducial system", Proceedings of the ICRA (International Conference on Robotics and Automation), Shanghai, May.
  5. Graphics and media lab (2013), GML camera calibration toolbox,
  6. Intel Co. (2015a), OpenCV,
  7. Intel Co. (2015b), The introduction of NUC,
  8. Jeon, H., Bang, Y. and Myung, H. (2011), "A paired visual servoing system for 6-DOF displacement measurement of structures", Smart Mater. Struct., 20(4), 045019.
  9. Jeon, H., Choi, S., Shin, J.U., Kim, Y. and Myung, H. (2017), "High-speed 6-DOF structural displacement monitoring by fusing ViSP (Visually Servoed Paired structured light system) and IMU with extended Kalman filter", Struct. Control. Health Monit., 24(6), e1926.
  10. Jeon, H., Kim, Y., Lee, D. and Myung, H. (2014), "Vision-based remote 6-DOF structural displacement monitoring system using a unique marker", Smart Struct. Syst., 13(16), 927-942.
  11. Jeon, H., Myeong, W., Shin, J.U., Park, J.W., Jung H.J. and Myung, H. (2014), "Experimental validation of ViSP (Visually Servoed Paired Structured Light System) for structural displacement monitoring", IEEE/ASME T. Mech., 19(5), 1603-1611.
  12. Jeon, H., Shin, J.U. and Myung, H. (2012), "Incremental displacement estimation of structures using paired structured light", Smart Struct. Syst, 9(3), 273-286.
  13. Jeon, H., Shin, J.U. and Myung, H. (2013), "The displacement estimation error back-propagation (DEEP) method for a multiple structural displacement monitoring system", Meas. Sci. Tech., 24(4), 045104.
  14. Ji, Y.F. and Chang, C.C. (2008), "Nontarget stereo vision technique for spatiotemporal response measurement of line-like structures", J. Eng. Mech. - ASCE, 134(6), 466-474.
  15. Lee, D., Jeon, H. and Myung, H. (2012), "Vision-based 6-DOF displacement measurement of structures with a planar marker." Proceedings of the SPIE (International Society for Optics and Photonics) Smart Structures/NDE, San Diego, April.
  16. Lee, D., Jeon, H., and Myung, H. (2014), "Pose-graph optimized displacement estimation for structural displacement monitoring", Smart Mater. Struct., 14(5), 943-960.
  17. Lee, J.J. and Shinozuka, M. (2006), "Real-time displacement measurement of a flexible bridge using digital image processing techniques", Exp. Mech., 46(1), 105-114.
  18. Logitech Co. (2013), The introduction of webcam,
  19. Marecos, J., Castanheira, M. and Trigo, J. (1969), "Field observation of Tagus river suspension bridge", J. Struct. Div.-ASCE, 95(4), 555-583.
  20. Myeong, W., Choi, S. and Myung, H. (2015), "Monte Carlo Localization and multiple vision sensor based 6-DOF displacement measurement system for the rendezvous of PC bridge members", Proceedings of the International Workshop on Structural Health Monitoring, California, September.
  21. Myeong, W., Lee, D., Kim, H. and Myung, H. (2014), "Visionbased guide system for rendezvous of PC bridge members using a planar marker", Proceedings of the 4th International Symposium on Life-Cycle Civil Engineering, Tokyo, November.
  22. Myung, H., Lee, S. and Lee, B.J. (2011), "Paired structured light for structural health monitoring robot system", Struct. Health Monit., 10(1), 49-64.
  23. Olaszek, P. (1999), "Investigation of the dynamic characteristic of bridge structures using a computer vision method", Measurement, 25(3), 227-236.
  24. Park, J.W., Lee, J.J., Jung, H.J. and Myung, H. (2010), "Visionbased displacement measurement method for high-rise building structures using partitioning approach", NDT & E Int., 43(7), 642-647.
  25. Pheng, L.S. and Chuan, C.J. (2001), "Just-in-time management in precast concrete construction: A survey of the readiness of main contractors in Singapore", Integ. Manufact. Syst., 12(6-7), 416-429.
  26. SENA Co. (2015), User manual of Parani-UD 100,
  27. The Mathworks, Inc. (2015), Single Camera Calibration app,
  28. Thorlabs, Inc. (2015), Thorlab's V21 photonics catalog,
  29. Thrun, S., Fox, D., Burgard, W. and Dellaert, F. (2001), "Roust Monte Carlo localization for mobile robots", Artif. Intell., 128(1-2), 99-141
  30. Vincent, L., Francesc, M.N. and Pascal, F. (2008), "EPnP: An Accurate O(n) Solution to the PnP Problem", Int. J. Comput. Vision, 81(2), 155-166.
  31. Wahbeh, A.M., Caffrey, J.P. and Masri, S.F. (2003), "A visionbased approach for the direct measurement of displacements in vibrating systems", Smart Mater. Struct., 12(5), 785-794.
  32. Yee, A.A. and Chuan, C.J. (2001), "Social and environmental benefits of precast concrete technology", J. Prestressed Concrete Institute, 46(3), 14-19.
  33. Yuko, U. and Hideo, S. (2007), "Improvement of accuracy for 2D marker-based tracking using particle filter", Proceedings of the Int'l Conference on on Artificial Reality and Telexistence 2007 (ICAT), Denmark, November.