@techreport{oai:ipsj.ixsq.nii.ac.jp:00233856,
 author = {Han, Lin and Atsushi, Nomura and Kota, Tsubouchi and Nobuhiko, Nishio and Masamichi, Shimosaka and Han, Lin and Atsushi, Nomura and Kota, Tsubouchi and Nobuhiko, Nishio and Masamichi, Shimosaka},
 issue = {9},
 month = {May},
 note = {As a promising device-free solution, wireless sensing techniques have been applied to various applications while addressing privacy concerns associated with traditional computer vision-based methods. There has been limited research focusing on the use of UWB CIR for activity recognition and showing improved performance over Wi-Fi CSI. However, previous studies using one-shot CIR cannot correctly capture the variations inherent in dynamic activities. This research proposes a device-free activity recognition approach by utilizing multi-shot CIRs, consisting of several CIRs arranged in a time series, in order to cover the transition of activities. And three variants of wavelet denoising across various dimensions are introduced to remove noise on signal. Experiments were conducted with horizontal and vertical device settings to test the sensing performance in different scenarios. The results were also compared with Wi-Fi CSI at the same frequency to benchmark its effectiveness., As a promising device-free solution, wireless sensing techniques have been applied to various applications while addressing privacy concerns associated with traditional computer vision-based methods. There has been limited research focusing on the use of UWB CIR for activity recognition and showing improved performance over Wi-Fi CSI. However, previous studies using one-shot CIR cannot correctly capture the variations inherent in dynamic activities. This research proposes a device-free activity recognition approach by utilizing multi-shot CIRs, consisting of several CIRs arranged in a time series, in order to cover the transition of activities. And three variants of wavelet denoising across various dimensions are introduced to remove noise on signal. Experiments were conducted with horizontal and vertical device settings to test the sensing performance in different scenarios. The results were also compared with Wi-Fi CSI at the same frequency to benchmark its effectiveness.},
 title = {Exploring Passive Activity Recognition using Multi-shot UWB CIRs},
 year = {2024}
}