TY - GEN
T1 - TripleM:Multidimensional Feature Separation of Multiple Gestures in Multi-Person Scenarios Based on FMCW Radar
AU - Jiang, Han
AU - An, Hongyang
AU - Li, Haoyu
AU - Wu, Junjie
AU - Li, Zhongyu
AU - Yang, Jianyu
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - A remarkable process has been made in hand gesture recognition based on radar sensors, which has potential application in human-computer interaction. However, existing research is mostly conducted for only one hand gesture in the sensor's field of view, leading to limitations in some practical scenarios when multiple gestures exist simultaneously. In this paper, we propose a method to estimate the number of multiple gestures precisely in multi-person scenarios firstly, then separates the mixed blind source signals to acquire each motion signal. Finally, we extract multidimensional features for each separated gesture. Extensive experiments are carried out based on commer-cial frequency modulated continuous wave (FMCW) single-input multi-output (SIMO) millimeter-wave radar systems to verify the effectiveness of this approach.
AB - A remarkable process has been made in hand gesture recognition based on radar sensors, which has potential application in human-computer interaction. However, existing research is mostly conducted for only one hand gesture in the sensor's field of view, leading to limitations in some practical scenarios when multiple gestures exist simultaneously. In this paper, we propose a method to estimate the number of multiple gestures precisely in multi-person scenarios firstly, then separates the mixed blind source signals to acquire each motion signal. Finally, we extract multidimensional features for each separated gesture. Extensive experiments are carried out based on commer-cial frequency modulated continuous wave (FMCW) single-input multi-output (SIMO) millimeter-wave radar systems to verify the effectiveness of this approach.
KW - Multi-gestures
KW - blind source separation (BSS)
KW - millimeter-wave radar
KW - multidimensional features
KW - source number estimation
UR - https://www.scopus.com/pages/publications/85163720023
U2 - 10.1109/RadarConf2351548.2023.10149780
DO - 10.1109/RadarConf2351548.2023.10149780
M3 - 会议稿件
AN - SCOPUS:85163720023
T3 - Proceedings of the IEEE Radar Conference
BT - RadarConf23 - 2023 IEEE Radar Conference, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Radar Conference, RadarConf23
Y2 - 1 May 2023 through 5 May 2023
ER -