Skip to main content

Virtual Try-On Using Kinect and HD Camera

  • Conference paper
Motion in Games (MIG 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7660))

Included in the following conference series:

Abstract

We present a virtual try-on system - EON Interactive Mirror - that employs one Kinect sensor and one High-Definition (HD) Camera. We first overview the major technical components for the complete virtual try-on system. We then elaborate on several key challenges such as calibration between the Kinect and HD cameras, and shoulder height estimation for individual subjects. Quality of these steps is the key to achieving seamless try-on experience for users. We also present performance comparison of our system implemented on top of two skeletal tracking SDKs: OpenNI and Kinect for Windows SDK (KWSDK). Lastly, we discuss our experience in deploying the system in retail stores and some potential future improvements.

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 39.99
Price excludes VAT (USA)
  • Available as 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Fitnect, http://www.fitnect.hu/

  2. Kinect for Windows, http://www.microsoft.com/en-us/kinectforwindows/

  3. Opencv, http://opencv.org/

  4. Trimirror, http://www.youtube.com/user/triMirrorTV

  5. Baak, A., Müller, M., Bharaj, G., Seidel, H.P., Theobalt, C.: A data-driven approach for real-time full body pose reconstruction from a depth camera. In: IEEE 13th International Conference on Computer Vision (ICCV), pp. 1092–1099 (2011)

    Google Scholar 

  6. Bailly, G., Müller, J., Rohs, M., Wigdor, D., Kratz, S.: Shoesense: a new perspective on gestural interaction and wearable applications. In: CHI 2012, pp. 1239–1248 (2012)

    Google Scholar 

  7. Benko, H., Jota, R., Wilson, A.D.: Miragetable: Freehand interaction on a projected augmented reality tabletop. In: CHI 2012 (2012)

    Google Scholar 

  8. Hilliges, O., Kim, D., Izadi, S., Weiss, M., Wilson, A.D.: Holodesk: Direct 3d interactions with a situated see-through display. In: Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems, CHI 2012 (2012)

    Google Scholar 

  9. Izadi, S., Newcombe, R.A., Kim, D., Hilliges, O., Molyneaux, D., Hodges, S., Kohli, P., Shotton, J., Davison, A.J., Fitzgibbon, A.: Kinectfusion: real-time dynamic 3d surface reconstruction and interaction. In: SIGGRAPH 2011 Talks, Article 23 (2011)

    Google Scholar 

  10. Kim, K., Bolton, J., Girouard, A., Cooperstock, J., Vertegaal, R.: Telehuman: effects of 3d perspective on gaze and pose estimation with a life-size cylindrical telepresence pod. In: CHI 2012, pp. 2531–2540 (2012)

    Google Scholar 

  11. Schwarz, L.A., Mkhitaryan, A., Mateus, D., Navab, N.: Estimating human 3d pose from time-of-flight images based on geodesic distances and optical flow. In: IEEE Conference on Automatic Face and Gesture Recognition (FG), pp. 700–706 (2011)

    Google Scholar 

  12. Shotton, J., Fitzgibbon, A.W., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-time human pose recognition in parts from single depth images. In: CVPR, pp. 1297–1304 (2011)

    Google Scholar 

  13. Weise, T., Bouaziz, S., Li, H., Pauly, M.: Realtime performance-based facial animation. ACM Trans. Graph. 30(4), Article 77 (2011)

    Google Scholar 

  14. Ye, M., Wang, X., Yang, R., Ren, L., Pollefeys, M.: Accurate 3d pose estimation from a single depth image. In: ICCV, pp. 731–738 (2011)

    Google Scholar 

  15. Zhu, Y., Dariush, B., Fujimura, K.: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2008 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Giovanni, S., Choi, Y.C., Huang, J., Khoo, E.T., Yin, K. (2012). Virtual Try-On Using Kinect and HD Camera. In: Kallmann, M., Bekris, K. (eds) Motion in Games. MIG 2012. Lecture Notes in Computer Science, vol 7660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34710-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34710-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34709-2

  • Online ISBN: 978-3-642-34710-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics