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Gesture Spotting Using Fuzzy Garbage Model and User Adaptation

Author

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  • Seung-Eun Yang

    (Korea Aerospace Research Institute, Korea)

  • Kwang-Hyun Park

    (Kwangwoon University, Korea)

  • Zeungnam Bien

    (Ulsan National Institute of Science and Technology, Korea)

Abstract

Thanks to the rapid advancement of human-computer interaction technologies it is becoming easier for the elderly and/or people with disabilities to operate various electrical systems. Operation of home appliances by using a set of predefined hand gestures is an example. However, hand gesture recognition may fail when the predefined command gestures are similar to some ordinary but meaningless behaviors of the user. This paper uses a gesture spotting method to recognize a designated gesture from other similar gestures. A fuzzy garbage model is proposed to provide a variable reference value to determine whether the user’s gesture is the command gesture or not. Further, the authors propose two-stage user adaptation to enhance recognition performance: that is, off-line (batch) adaptation for inter-person variation and on-line (incremental) adaptation for intra-person variation. For implementation of the two-stage adaptation method, a genetic algorithm (GA) and the steepest descent method are adopted for each stage. Experimental results were obtained for 5 different users with left and up command gestures.

Suggested Citation

  • Seung-Eun Yang & Kwang-Hyun Park & Zeungnam Bien, 2011. "Gesture Spotting Using Fuzzy Garbage Model and User Adaptation," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 1(3), pages 47-65, July.
    • Handle: RePEc:igg:jfsa00:v:1:y:2011:i:3:p:47-65
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    Cited by:

    1. Toly Chen & Yi-Chi Wang & Zhirong Lin, 2017. "Predictive distant operation and virtual control of computer numerical control machines," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1061-1077, June.

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