Volume 12 Issue 4
Aug.  2023
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Article Navigation >  Journal of Radars  > 2023  >  12(4): 892-905
QIAN Guang, QIAN Kun, GU Xiaowen, et al. Integrated chip technologies for microwave photonics[J]. Journal of Radars, 2019, 8(2): 262–280. doi: 10.12000/JR19044
Citation: DU Lan, CHEN Xiaoyang, SHI Yu, et al. MMRGait-1.0: A radar time-frequency spectrogram dataset for gait recognition under multi-view and multi-wearing conditions[J]. Journal of Radars, 2023, 12(4): 892–905. doi: 10.12000/JR22227
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MMRGait-1.0: A Radar Time-frequency Spectrogram Dataset for Gait Recognition under Multi-view and Multi-wearing Conditions

DOI: 10.12000/JR22227

  • National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Funds:  The National Natural Science Foundation of China (U21B2039)
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  • Corresponding author: DU Lan, dulan@mail.xidian.edu.cn
  • Received Date: 2022-11-24
  • Rev Recd Date: 2023-02-10
    • Available Online: 2023-02-14
  • Publish Date: 2023-03-06
    Abstract
  • As a biometric technology, gait recognition is usually considered a retrieval task in real life. However, because of the small scale of the existing radar gait recognition dataset, the current studies mainly focus on classification tasks and only consider the situation of a single walking view and the same wearing condition, limiting the practical application of radar-based gait recognition. This paper provides a radar gait recognition dataset under multi-view and multi-wearing conditions; the dataset uses millimeter-wave radar as a sensor to collect the time-frequency spectrogram data of 121 subjects walking along views under multiple wearing conditions. Eight views were collected for each subject, and ten sets were collected for each view. Six of the ten sets are dressed normally, two are dressed in coats, and the last two are carrying bags. Meanwhile, this paper proposes a method for radar gait recognition based on retrieval tasks. Experiments are conducted on this dataset, and the experimental results can be used as a benchmark to facilitate further research by related scholars on this dataset.

     

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    • References(26)
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