Skip to main content

Natural Interaction with 3D Content on Mobile AR Systems Using Gesture Recognition

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9769))

Abstract

We present a mobile AR interaction system where the user can naturally interact with and manipulate 3D content by recognizing discrete in-air gestures and temporal poses of a hand in front of the camera. Our system consists of established image processing, pose estimation and AR rendering steps, and a novel fingertip detection algorithm that can run real-time on off-the-shelf mobile devices with the use of an external depth camera. We also present an application prototype implemented on a tablet with a mounted IR structured-lighting depth camera.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • 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

Learn about institutional subscriptions

Notes

  1. 1.

    http://structure.io/.

References

  1. Malik, S., McDonald, C., Roth, G.: Tracking for interactive pattern-based augmented reality. In: ISMAR 2002, pp. 117–126 (2002)

    Google Scholar 

  2. Dormfuller-Ulhaas, K., Schmalstieg, D.: Finger tracking for interaction in augmented environments. In: ISAR 2001, pp. 55–64 (2001)

    Google Scholar 

  3. Ren, Z., Yuan, J., Meng, J., Zhang, Z.: Robust part-based hand gesture recognition using Kinect sensor. Multimed. IEEE Trans. 15(5), 1110–1120 (2013)

    Article  Google Scholar 

  4. Oikonomides, I., Kyriazis, N., Argyros, A.A.: Full DOF tracking of hand interacting with an object by modelling occlusions and physical constraints. In: IEEE International Conference on Computer Vision, pp. 2088–2095 (2011)

    Google Scholar 

  5. Malima, A., Özgür, E., Çetin, M.: A fast algorithm for vision-based hand gesture recognition for robot control. In: IEEE Conference on Signal Processing and Communications Applications, Antalya, Turkey (2006)

    Google Scholar 

  6. Hu, M.: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theor. 8(2), 179–187 (1962)

    Article  MATH  Google Scholar 

  7. Song, J., Sörös, G., Pece, F., Hilliges, O.: Real-time hand gesture recognition on unmodified wearable devices. In: IEEE Conference on Computer Vision and Pattern Recognition (2015)

    Google Scholar 

  8. Kyriazakos, V., Moustakas, K.: A user-perspective view for mobile AR systems using discrete depth segmentation. In: 2015 International Conference on Cyberworlds (CW), Visby, pp. 69–72 (2015)

    Google Scholar 

  9. Serra, G., Camurri, M., Baraldi, L., Benedetti, M., Cucchiara, R.: Hand segmentation for gesture recognition in EGO-vision. In: Proceedings of the 3rd ACM International Workshop on Interactive Multimedia on Mobile and Portable Devices, pp. 31–36 (2013)

    Google Scholar 

Download references

Acknowledgements

This work has been supported by the Greek Secretariat for Research and Technology Bilateral Collaboration Project MOMIRAS (ISR-3215).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Konstantinos Moustakas .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Kyriazakos, V., Nikolakis, G., Moustakas, K. (2016). Natural Interaction with 3D Content on Mobile AR Systems Using Gesture Recognition. In: De Paolis, L., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2016. Lecture Notes in Computer Science(), vol 9769. Springer, Cham. https://doi.org/10.1007/978-3-319-40651-0_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40651-0_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40650-3

  • Online ISBN: 978-3-319-40651-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics