Skip to main content

A Wireless Kinect Sensor Network System for Virtual Reality Applications

  • Conference paper
  • First Online:
Advances in Computer Science and Ubiquitous Computing (UCAWSN 2016, CUTE 2016, CSA 2016)

Abstract

Currently, Microsoft Kinect, a motion sensing input device, has been developed quickly in research for human gesture recognition. The Kinect integrating into games and Virtual Reality (VR) improves the immersion sense and natural user experience. However, the Kinect is able to accurately measure a user within five meters, while the user must face to the sensor. To solve this problem, this paper develops a wireless Kinect sensor network system to detect users at several viewports. This system utilizes multiple Kinect clients to sense user’s gesture information, which is transmitted to a VR managing server for the integration of the distributed sensing datasets. Different from the VR application with a single Kinect, our proposed system is able to support the user’s walking around no matter whether he is facing the sensors or not. Meanwhile, we developed a virtual boxing VR game with two Kinects, Samsung Gear VR and Unity3D environment, which verified the effective performance of the proposed system.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

References

  1. Ales, P., Oldrich, V., Martin, V., et al.: Use of the image and depth sensors of the Microsoft Kinect for the detection of gait disorders. Neural Comput. Appl. 26, 1621–1629 (2015)

    Article  Google Scholar 

  2. Mohammed, A., Ahmed, S.: Kinect-Based Humanoid Robotic Manipulator for Human Upper Limbs Movements Tracking. Intell. Control Autom. 6, 29–37 (2015)

    Article  Google Scholar 

  3. Chen, H., Dai, Z., Liu, Z., et al.: An image-to-class dynamic time warping approach for both 3D static and trajectory hand gesture recognition. Pattern Recogn. 55, 137–147 (2016)

    Article  Google Scholar 

  4. Chen, Y., Dang, G., Chen, Z., et al.: Fast capture of personalized avatar using two Kinects. J. Manufact. Syst. 33, 233–240 (2014)

    Article  Google Scholar 

  5. Sun, S., Kuo, C., Chang, P.: People tracking in an environment with multiple depth cameras: a skeleton-based pairwise trajectory matching scheme. J. Vis. Commun. Image Represent. 35, 36–54 (2016)

    Article  Google Scholar 

  6. Chua, S.L., Foo, L.K.: Sensor selection in smart homes. Procedia Comput. Sci. 69, 116–124 (2015)

    Article  Google Scholar 

  7. Sevrin, L., Noury, N., Abouchi, N., et al.: Preliminary results on algorithms for multi-kinect trajectory fusion in a living lab. IRBM 36, 361–366 (2015)

    Article  Google Scholar 

Download references

Acknowledgment

This research was supported by the National Natural Science Foundation of China (61503005), by the research foundation of NCUT (XN070027, XN001-93, and XN001-83), by Advantageous Subject Cultivation Fund of NCUT, and by SRF for ROCS, SEM.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Song .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Li, M., Song, W., Song, L., Huang, K., Xi, Y., Cho, K. (2017). A Wireless Kinect Sensor Network System for Virtual Reality Applications. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3023-9_10

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3022-2

  • Online ISBN: 978-981-10-3023-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics