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Face identification using millimetre-wave radar sensor data

Authors
Kim, J.Lee, J. -E.Lim, H. -S.Lee, S.
Issue Date
Sep-2020
Publisher
WILEY
Citation
ELECTRONICS LETTERS, v.56, no.20, pp 1077 - +
Journal Title
ELECTRONICS LETTERS
Volume
56
Number
20
Start Page
1077
End Page
+
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/70088
DOI
10.1049/el.2020.1822
ISSN
0013-5194
1350-911X
Abstract
In this Letter, the authors propose a face identification method using radar sensor data. They use a frequency-modulated continuous wave radar sensor that utilises a centre frequency of 61 GHz and a bandwidth of 6 GHz. Then, they accumulate radar data by transmitting and receiving radar signals on human faces. Finally:, they use a convolutional neural network (CNN) to distinguish radar signals reflected from different human faces. In this network, signals received from multiple antenna elements are synthesised in parallel to make the radar signals into an image that is the input form of the CNN. The accuracy of face recognition through the CNN is > 98%. In addition, they also collect radar data when the same subjects wear cotton masks. Within their entire dataset, wearing a mask does not significantly affect the accuracy of the radar-based face recognition method.
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창의ICT공과대학 (전자전기공학부)
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