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    User identification approach based on simple gestures

    Access Status
    Fulltext not available
    Authors
    Guna, J.
    Stojmenova, E.
    Lugmayr, Artur
    Humar, I.
    Pogacnik, M.
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Guna, J. and Stojmenova, E. and Lugmayr, A. and Humar, I. and Pogacnik, M. 2014. User identification approach based on simple gestures. Multimedia Tools and Applications. 71 (1): pp. 179-194.
    Source Title
    Multimedia Tools and Applications
    DOI
    10.1007/s11042-013-1635-1
    ISSN
    1380-7501
    URI
    http://hdl.handle.net/20.500.11937/42853
    Collection
    • Curtin Research Publications
    Abstract

    We present an intuitive, implicit, gesture based identification system suited for applications such as the user login to home multimedia services, with less strict security requirements. The term “implicit gesture” in this work refers to a natural physical hand manipulation of the control device performed by the user, who picks it up from its neutral motionless position or shakes it. For reference with other related systems, explicit and well defined identification gestures were used. Gestures were acquired by an accelerometer sensor equipped device in a form of the Nintendo WiiMote remote controller. A dynamic time warping method is used at the core of our gesture based identification system. To significantly increase the computational efficiency and temporal stability, the “super-gesture” concept was introduced, where acceleration features of multiple gestures are combined in only one super-gesture template per each user. User evaluation spanning over a period of 10 days and including 10 participants was conducted. User evaluation study results show that our algorithm ensures nearly 100 % recognition accuracy when using explicit identification signature gestures and between 88 % and 77 % recognition accuracy when the system needs to distinguish between 5 and 10 users, using the implicit “pick-up” gesture. Performance of the proposed system is comparable to the results of other related works when using explicit identification gestures, while showing that implicit gesture based identification is also possible and viable.

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