TY - GEN
T1 - ATTENTION-BASED DUAL-STREAM VISION TRANSFORMER FOR RADAR GAIT RECOGNITION
AU - Chen, Shiliang
AU - He, Wentao
AU - Ren, Jianfeng
AU - Jiang, Xudong
N1 - Publisher Copyright:
© 2022 IEEE
PY - 2022
Y1 - 2022
N2 - Radar gait recognition is robust to light variations and less infringement on privacy. Previous studies often utilize either spectrograms or cadence velocity diagrams. While the former shows the time-frequency patterns, the latter encodes the repetitive frequency patterns. In this work, a dual-stream network with attention-based fusion is proposed to fully aggregate the discriminant information from these two representations. Both streams are analyzed through the Vision Transformer, which well captures the gait characteristics embedded in these representations. The proposed method is validated on a large benchmark dataset for radar gait recognition, showing that it significantly outperforms state-of-the-art solutions.
AB - Radar gait recognition is robust to light variations and less infringement on privacy. Previous studies often utilize either spectrograms or cadence velocity diagrams. While the former shows the time-frequency patterns, the latter encodes the repetitive frequency patterns. In this work, a dual-stream network with attention-based fusion is proposed to fully aggregate the discriminant information from these two representations. Both streams are analyzed through the Vision Transformer, which well captures the gait characteristics embedded in these representations. The proposed method is validated on a large benchmark dataset for radar gait recognition, showing that it significantly outperforms state-of-the-art solutions.
KW - Attention-based fusion
KW - Cadence velocity diagram
KW - Radar gait recognition
KW - Spectrogram
KW - Vision transformer
UR - http://www.scopus.com/inward/record.url?scp=85131251096&partnerID=8YFLogxK
U2 - 10.1109/ICASSP43922.2022.9746565
DO - 10.1109/ICASSP43922.2022.9746565
M3 - Conference contribution
AN - SCOPUS:85131251096
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 3668
EP - 3672
BT - 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Y2 - 23 May 2022 through 27 May 2022
ER -