Demo: Efficient Convolutional Neural Network for FMCW Radar Based Hand Gesture Recognition

被引：12
|
作者：
Cai, Xiaodong [1 ]
Ma, Jingyi [2 ]
Liu, Wei [2 ]
Han, Hemin [1 ]
Ma, Lili [1 ]
机构：
[1] Intel Corp, Shanghai, Peoples R China
[2] Intel Labs China, Beijing, Peoples R China
来源：
UBICOMP/ISWC'19 ADJUNCT: PROCEEDINGS OF THE 2019 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2019 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS | 2019年
关键词：
FMCW radar; hand gesture recognition; signal processing; Convolutional Neural Network;
D O I：
10.1145/3341162.3343768
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
FMCW radar could detect object's range, speed and Angle-of-Arrival, advantages are robust to bad weather, good range resolution, and good speed resolution. In this paper, we consider the FMCW radar as a novel interacting interface on laptop. We merge sequences of object's range, speed, azimuth information into single input, then feed to a convolution neural network to learn spatial and temporal patterns. Our model achieved 96% accuracy on test set and real-time test.
引用
收藏
页码：17 / 20
页数：4
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