239 / 2020-01-03 15:20:00
A Real-time Human Activity Recognition Method for TWR
Human Activity Recognition; through-the-wall radar; real-time; long short time memory network
Draft Rejected
Can Cheng / University of Electronic Science and Tech, China
Fei Ling / University of Electronic Science and Tech, China
Shisheng Guo / University of Electronic Science and Technology of China, China
Guolong Cui / University of Electronic Science and Technology of China (UESTC), China
Lingjiang Kong / University of Electronic Science and Technology of China (UESTC), China
Chao Jia / University of Electronic Science and Tech, China
Xiaobo Yang / University of Electronic Science and Technology of China, China
Human activity recognition (HAR) has long been a question of great interest in anti-terrorism and other applications. In recent years, radar has been one of
the most widely used sensing modality of detecting human motion and have been extensively used for HAR. This paper researches on blocked human activity description method and deep learning recognition algorithm. In order to obtain the real-time nature of recognition under the condition of through-wall probing scenario, we proposes a range profile sequence driven FC-SLSTM-FC end-to-end model, which employ random crop training method. Based on the architecture above, we process the actual radar data, finally achieve an average accuracy of 97.6%
and real-time output with delay of only milliseconds.
Important Date
  • Conference Date

    Jun 08

    2020

    to

    Jun 11

    2020

  • Jan 12 2020

    Draft paper submission deadline

  • Apr 15 2020

    Early Bird Registration

  • Dec 31 2020

    Registration deadline

Sponsored By
IEEE Signal Processing Society
Organized By
Zhejiang University
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