skip to main content
10.1145/2617841.2620710acmotherconferencesArticle/Chapter ViewAbstractPublication PagesvricConference Proceedingsconference-collections
research-article

Multi-sensor data fusion for hand tracking using Kinect and Leap Motion

Published:09 April 2014Publication History

ABSTRACT

Often presented as competing products on the market of low cost 3D sensors, the Kinect™ and the Leap Motion™ (LM) can actually be complementary in some scenario. We promote, in this paper, the fusion of data acquired by both LM and Kinect sensors to improve hand tracking performances. The sensor fusion is applied to an existing augmented reality system targeting the treatment of phantom limb pain (PLP) in upper limb amputees. With the Kinect we acquire 3D images of the patient in real-time. These images are post-processed to apply a mirror effect along the sagittal plane of the body, before being displayed back to the patient in 3D, giving him the illusion that he has two arms. The patient uses the virtual reconstructed arm to perform given tasks involving interactions with virtual objects. Thanks to the plasticity of the brain, the restored visual feedback of the missing arm allows, in some cases, to reduce the pain intensity. The Leap Motion brings to the system the ability to perform accurate motion tracking of the hand, including the fingers. By registering the position and orientation of the LM in the frame of reference of the Kinect, we make our system able to accurately detect interactions of the hand and the fingers with virtual objects, which will greatly improve the user experience. We also show that the sensor fusion nicely extends the tracking domain by supplying finger positions even when the Kinect sensor fails to acquire the depth values for the hand.

References

  1. B. Penelle, D. Mouraux, E. Brassinne, T. Tuna, A. Nonclercq, and N. Warzée. 3D augmented reality applied to the treatment of neuropathic pain. In Proc. 9th Intl Conf. on Disability, Virtual Reality and Assoc. Technologies, pages 61--68, Laval, France, September 2012. P M Sharkey, E Klinger (Eds).Google ScholarGoogle Scholar
  2. P. J. Besl and N. D. McKay. A method for registration of 3-D shapes. IEEE Trans. Pattern Anal. Mach. Intell., 14(2):239--256, February 1992. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. R. Bradski and A. Kaehler. Learning OpenCV, 1st Edition. O'Reilly Media, Inc., first edition, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. H. Flor. Phantom-limb pain: characteristics, causes, and treatment. The Lancet Neurology, 1(3):182--189, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  5. K. Khoshelham and S. O. Elberink. Accuracy and resolution of Kinect depth data for indoor mapping applications. Sensors, 12(12):1437--1454, February 2012.Google ScholarGoogle ScholarCross RefCross Ref
  6. G. L. Moseley. Using visual illusion to reduce at-level neuropathic pain in paraplegia. PAIN, 130(3):294--298, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  7. I. Oikonomidis, N. Kyriazis, and A. Argyros. Efficient model-based 3D tracking of hand articulations using Kinect. In Proceedings of the British Machine Vision Conference, pages 101.1--101.11. BMVA Press, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  8. V. S. Ramachandran and E. L. Altschuler. The use of visual feedback, in particular mirror visual feedback, in restoring brain function. Brain, 132(7):1693--1710, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  9. F. Weichert, D. Bachmann, B. Rudak, and D. Fisseler. Analysis of the accuracy and robustness of the Leap Motion controller. Sensors, 13(5):6380--6393, May 2013.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Multi-sensor data fusion for hand tracking using Kinect and Leap Motion

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        VRIC '14: Proceedings of the 2014 Virtual Reality International Conference
        April 2014
        193 pages
        ISBN:9781450326261
        DOI:10.1145/2617841

        Copyright © 2014 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 9 April 2014

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader