Context-Aware Information Based Ultrasonic Gesture Recognition Method

被引：2
|
作者：
Zhong X. [1 ,2 ,3 ,4 ]
Chen Y. [1 ,2 ,4 ]
Yu H. [1 ,2 ,3 ]
Yang X. [1 ,2 ,3 ,4 ]
Hu Z. [1 ,2 ,3 ,4 ]
机构：
[1] Research Center for Ubiquitous Computing Systems, Institute of Computing Technology Chinese Academy of Sciences, Beijing
[2] Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing
[3] Beijing Key Laboratory of Parkinson's Disease Research, Beijing
[4] University of Chinese Academy of Sciences, Beijing
来源：
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2018年 / 30卷 / 01期
关键词：
Context-aware; Gesture recognition; Human-computer interaction; Ultrasonic;
D O I：
10.3724/SP.J.1089.2018.16176
中图分类号：
学科分类号：
摘要：
The existing ultrasonic gesture recognition methods are usually vulnerable to invalid gestures and hardly to identify wrong classified gestures in real time. This paper presents a context-aware information based ultrasonic gesture recognition method. This method extracts effective gesture features using fast Fourier transform. Then the confidence of gestures is calculated by using extreme learning machine algorithm and softmax function. Context-aware information is transformed into gesture's context confidence by the defined probability transformation function simultaneously. Both gesture confidence and gesture's context confidence are combined to yield satisfactory recognition results by filtering invalid gestures and correcting wrong classified gestures finally. The results of extensive experiments show that the recognition accuracy of this method could reach 94.7%, which is 33.2% higher than the ultrasonic gesture recognition methods without context information. © 2018, Beijing China Science Journal Publishing Co. Ltd. All right reserved.
引用
收藏
页码：173 / 179
页数：6
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