Dynamic Hand Gesture Recognition Based on Parallel HMM Using Wireless Signals

被引：0
|
作者：
Xu, Jiabin [1 ]
Jiang, Ting [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Key Lab Universal Wireless Commun, Beijing, Peoples R China
来源：
COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS | 2018年 / 423卷
基金：
中国国家自然科学基金;
关键词：
Dynamic gesture recognition; Software defined radio; Time-series; Parallel HMM models; Wireless signals;
D O I：
10.1007/978-981-10-3229-5_80
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Dynamic hand gesture recognition plays an important role in human computer Interaction. This paper proposes a novel method for dynamic hand gesture recognition using wireless signals. Through the analysis of wireless frame structure, the preamble's signal of 802.11a is collected through Software Defined Radio platform and reserved as the data source. In addition, more than one time-domain feature sequences perform unique shape for different dynamic hand gesture. These sequences are split into single cycle (time-series) and the unavoidable electronic interference is reduced through discrete wavelet transform. At the same time, due to fuzziness of dynamic hand gesture, the amplitude and duration for the same dynamic hand gesture are not exactly same. Therefore, the parallel HMM models which represent for different hand gestures and features are built for recognition. The result shows that the average recognition rate is about 90.5% for dynamic hand gesture recognition.
引用
收藏
页码：749 / 757
页数：9
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