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access icon free Multiuser motion recognition system using smartphone LED luminescence

  • Author(s): Byung-Hun Oh 1 ; Jung-Hyun Kim 2 ; Kwang-Woo Chung 3 ; Kwang-Sook Hong 1
    • View affiliations
    • Affiliations: 1: School of Information and Communication Engineering, Sungkyunkwan University, 300, Chunchun-dong, Jangangu, Suwon, KyungKi-do 440-746, Republic of Korea;
      2: Central Technology Appraisal Institute, KOTEC, 11th Songdo-Centrod, Songdo-dong, Yeonsu-gu, Incheon 406-840, Republic of Korea;
      3: Department of Railway Operation System Engineering, Korea National University of Transportation, 157, CheoldobangmulgKwan-ro, Uiwang-si, Kyungki-do 437-763, Republic of Korea
  • Source: Volume 51, Issue 5, 05 March 2015, p. 388 – 390
    DOI:  10.1049/el.2014.4328 , Print ISSN 0013-5194, Online ISSN 1350-911X
© The Institution of Engineering and Technology
Received 10/12/2014, Published 23/02/2015
Errata or comment

A novel multiuser motion recognition system that uses a smartphone detection method and tracking interface is proposed. This multiuser motion recognition system provides a motion control interface between devices using an image-based object tracking algorithm through smartphone light-emitting diode (LED) luminescence. It requires just a universal serial bus (USB) camera and personal smartphone instead of expensive equipment to provide a motion control interface. It recognises the user's gestures by tracking three-dimensional (3D) distance and the rotation angle of the smartphone, which acts essentially as a controller in the user's hand.

Inspec keywords: multiuser detection; mobile computing; image motion analysis; smart phones; object tracking; object detection; gesture recognition; light emitting diodes

Other keywords: smartphone LED luminescence; universal serial bus; multiuser motion recognition system; light-emitting diode; motion control interface; 3D distance tracking; user gesture recognition; smartphone tracking interface; rotation angle tracking; image-based object tracking algorithm; USB camera; smartphone detection method

Subjects: Computer vision and image processing techniques; Mobile, ubiquitous and pervasive computing; Image recognition

References

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      • 4. Oikonomidis, I., Kyriazis, N., Argyros, A.A.: ‘Efficient model-based 3D tracking of hand articulations using kinect’. British Machine Vision Conf., Dundee, Scotland, September 2011, pp. 101.1–101.11.
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