Advertisement

Semi-automatic Initial Registration for the iRay System: A User Study

  • Tian Xie
  • Mohammad M. Islam
  • Alan B. Lumsden
  • Ioannis A. KakadiarisEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10325)

Abstract

Simultaneous localization and mapping based augmented reality (AR) is trending in mobile AR applications. With the help of depth sensors, both accuracy and speed have improved. However, the method that performs the initial registration to align virtual objects with real scenery is not well developed, especially for some applications requiring very accurate registration (e.g., systems used in medical applications). For the iRay system, which is a mobile AR system using the Structure Sensor, we propose to use an iterative closest point algorithm to initially register the scanned mesh with the torso surface obtained pre-operatively, and then use SLAM to track pose. In this paper, a semi-automatic initial registration strategy is evaluated by a user study. This strategy is designed to help the user modify the selection of the 3D scanning area, so that the errors introduced by subjective differences can be reduced. The results indicate that the proposed strategy helps the users improve initial registration quality and reduces the average needed time.

Keywords

Medical AR Mobile AR 3D registration User study 

Notes

Acknowledgements

This work was funded in part by the Methodist Research Institute and the UH Hugh Roy and Lillie Cranz Cullen Endowment Fund. All statements of fact, opinion or conclusions contained herein are those of the authors and should not be construed as representing the official views or policies of the sponsors.

References

  1. 1.
    Coquillart, S., Brunnett, G., Welch, G.: Virtual Realities: Dagstuhl Seminar 2008. Springer Science & Business Media, Berlin (2010). doi: 10.1007/978-3-211-99178-7 Google Scholar
  2. 2.
    van den Hengel, A., Hill, R., Ward, B., Dick, A.: In situ image-based modeling. In: Proceedings 8th IEEE International Symposium on Mixed and Augmented Reality, Orlando, FL, USA, pp. 107–110 (2009). doi: 10.1109/ISMAR.2009.5336482
  3. 3.
    Langlotz, T., Mooslechner, S., Zollmann, S., Degendorfer, C., Reitmayr, G., Schmalstieg, D.: Sketching up the world: in situ authoring for mobile augmented reality. Pers. Ubiquit. Comput. 16(6), 623–630 (2012). doi: 10.1007/s00779-011-0430-0 CrossRefGoogle Scholar
  4. 4.
  5. 5.
  6. 6.
    Kakadiaris, I.A., Islam, M.M., Xie, T., Nikou, C., Lumsden, A.B.: iRay: mobile AR using structure sensor. In: Proceedings 15th IEEE International Symposium on Mixed and Augmented Reality, Merida, Mexico (2016)Google Scholar
  7. 7.
    Structure sensor. https://structure.io
  8. 8.
    Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J., Kohi, P., Shotton, J., Hodges, S., Fitzgibbon, A.: KinectFusion: real-time dense surface mapping and tracking. In: Proceedings 10th IEEE International Symposium on Mixed and Augmented Reality, Basel, Switzerland, pp. 127–136. (2011). doi: 10.1109/ISMAR.2011.6092378
  9. 9.
    Newcombe, R.A., Fox, D., Seitz, S.M.: DynamicFusion: reconstruction and tracking of non-rigid scenes in real-time. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA, pp. 343–352 (2015)Google Scholar
  10. 10.
    Shamir, R.R., Joskowicz, L., Spektor, S., Shoshan, Y.: Localization and registration accuracy in image guided neurosurgery: a clinical study. Int. J. Comput. Assist. Radiol. Surg. 4(1), 45–52 (2009). doi: 10.1007/s11548-008-0268-8 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Computational Biomedicine Lab, Department of Computer ScienceUniversity of HoustonHoustonUSA
  2. 2.Methodist Research InstituteHoustonUSA

Personalised recommendations