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Gesture Spotting Using Fuzzy Garbage Model and User Adaptation

Gesture Spotting Using Fuzzy Garbage Model and User Adaptation

Seung-Eun Yang, Kwang-Hyun Park, Zeungnam Bien
Copyright: © 2013 |Pages: 19
ISBN13: 9781466618701|ISBN10: 1466618701|EISBN13: 9781466618718
DOI: 10.4018/978-1-4666-1870-1.ch009
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MLA

Yang, Seung-Eun, et al. "Gesture Spotting Using Fuzzy Garbage Model and User Adaptation." Contemporary Theory and Pragmatic Approaches in Fuzzy Computing Utilization, edited by Toly Chen, IGI Global, 2013, pp. 120-138. https://doi.org/10.4018/978-1-4666-1870-1.ch009

APA

Yang, S., Park, K., & Bien, Z. (2013). Gesture Spotting Using Fuzzy Garbage Model and User Adaptation. In T. Chen (Ed.), Contemporary Theory and Pragmatic Approaches in Fuzzy Computing Utilization (pp. 120-138). IGI Global. https://doi.org/10.4018/978-1-4666-1870-1.ch009

Chicago

Yang, Seung-Eun, Kwang-Hyun Park, and Zeungnam Bien. "Gesture Spotting Using Fuzzy Garbage Model and User Adaptation." In Contemporary Theory and Pragmatic Approaches in Fuzzy Computing Utilization, edited by Toly Chen, 120-138. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-1870-1.ch009

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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.

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