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Article type: Research Article
Authors: Zhou, Zhihenga; * | Dai, Yukuna | Li, Weishengb
Affiliations: [a] South China University of Technology, Guangzhou, China | [b] Chongqing University, Chongqing, China
Correspondence: [*] Corresponding author. Zhiheng Zhou, South China University of Technology, No.381 Wushan Road, Guangzhou, China. E-mail: zhouzh@scut.edu.cn.
Abstract: This paper proposes global template dynamic time warping (GTDTW) algorithm for gesture recognition with the wearable gloves. The method is applied to both isolated and continuous gesture recognition. A gesture segmentation system based on GTDTW is also proposed for continuous gesture recognition. The global template is obtained based on statistical methods. For a defined gesture, states which have a large proportion are selected as important states. They form the global template for the defined gesture. Global template more fully expresses the characteristics of the defined gesture which can improve gesture recognition rate. Global template also has a smaller length than normal template of Dynamic Time Warping (DTW) so that time consumption of GTDTW is low and gesture recognition system has a better real-time performance. Experimental evaluations on both isolated and continuous gesture recognition show the effectiveness of the proposed method. The time consumption is obviously reduced and recognition rate is improved that up to 98.8% for isolated gesture recognition. For continuous gesture recognition, the proposed method has high segmentation rate and recognition rate is up to 95.6%.
Keywords: Global template, dynamic time warping, wearable gloves, isolated gesture recognition, continuous gesture recognition
DOI: 10.3233/JIFS-171618
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1969-1978, 2018
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