Paper Info
Title
Spectrum-Based Hand Gesture Recognition Using Millimeter-Wave Radar Parameter Measurements.
Abstract
Radar sensors offer several advantages over optical sensors in the gesture recognition for remote control of electronic devices. In this paper, we investigate the feasibility of human gesture recognition using the spectra of radar measurement parameters. With the combination of radar theory and classification methods, we found that the frequencies of different gestures' parameters could be utilized as features for gesture recognition. Six kinds of periodic dynamic gestures are designed to avoid the complexity of defining and extracting the start and end of the dynamic gesture. In addition to the frequency ratio, we also extracted some features related to motion range and detection coherence to eliminate the interferences brought by the unintended gestures. The decision tree classifier designed on the basis of experimental phenomena can guarantee effective classification between different gestures, and in general, the correct recognition rate of each gesture is higher than 90%. Finally, we collected the position and the Doppler velocity information of hand for classification by a W-band millimeter wave radar in the experiment and verified the usability of the proposed method.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2923122
IEEE ACCESS
Keywords
Field
DocType
Gesture recognition,millimeter-wave,feature extraction,decision tree
Radar,Computer vision,Extremely high frequency,Remote control,Gesture,Computer science,Usability,Gesture recognition,Coherence (physics),Artificial intelligence,Decision tree learning,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Changjiang Liu143.58
Yuanhao Li23612.62
Dongyang Ao3255.99
Haiyan Tian400.34