Gesture Recognition Using mm-Wave Sensor for Human-Car Interface

被引：95

作者：

Smith, Karly A. ^{[1
]}

Csech, Clement ^{[2
]}

Murdoch, David ^{[3
]}

Shaker, George ^{[3
,4
]}

机构：

[1] Univ Waterloo, Dept Syst Design Engn, Waterloo, ON N2L 3G1, Canada

[2] Univ Technol Compiegne, Dept Biomech & Bioengn, F-60200 Compiegne, France

[3] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada

[4] Univ Waterloo, Dept Mech & Mechatron Engn, Waterloo, ON N2L 301, Canada

来源：

IEEE SENSORS LETTERS | 2018年 / 2卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Microwave/millimeter wave sensors; human-car interface; 60 GHz mm-wave radar; gesture sensing; random forest classifier; machine learning;

D O I：

10.1109/LSENS.2018.2810093

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：

This article details the development of a gesture recognition technique using a mm-wave radar sensor for in-car infotainment control. Gesture recognition is becoming a more prominent form of human-computer interaction and can be used in the automotive industry to provide a safe and intuitive control interface that will limit driver distraction. We use a 60 GHz mm-wave radar sensor to detect precise features of fine motion. Specific gesture features are extracted and used to build a machine learning engine that can perform real-time gesture recognition. This article discusses the user requirements and in-car environmental constraints that influenced design decisions. Accuracy results of the technique are presented, and recommendations for further research and improvements are made.

引用

页数：4

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