| Presentation | 2020-12-15 Classification of pedestrians existing in visible or blind areas using Doppler radar Sora Hayashi, Daiki Isobe, Kenshi saho, Masao Masugi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this report, the walking positions of pedestrians, whether they are directly visible from the observation point or in the blind spot areas such as behind a wall, were evaluated by the Doppler radar. An LSTM (Long Short-Term Memory) model, which is a kind of deep learning neural network, was used in our study. Time-series data of the gait velocity, which correspond to the legs and torso of pedestrians, and time transition of received power were input to LSTM. Experimental results confirmed that our method is effective for estimating the positions of pedestrians and classifying their gait patterns in each area. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Doppler Radar / Gait Analysis / Monitoring of Blind Area / Deep Learning / Long Short-Term Memory |
| Paper # | WBS2020-29,ITS2020-25,RCC2020-32 |
| Date of Issue | 2020-12-07 (WBS, ITS, RCC) |
| Conference Information | |
| Committee | ITS / WBS / RCC |
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| Conference Date | 2020/12/14(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | ITS Communications, Reliable Communication and Control, Radar and Sensing, etc. |
| Chair | Tomotaka Wada(Kansai Univ.) / Masanori Hamamura(Kochi Univ. of Tech.) / HUAN-BANG LI(NICT) |
| Vice Chair | Yusuke Takatori(Kanagawa Inst. of Tech.) / Hiroyuki Hatano(Mie Univ.) / Takashi Shono(INTEL) / Masahiro Fujii(Utsunomiya Univ.) / Shunichi Azuma(Nagoya Univ.) / Koji Ishii(Kagawa Univ.) |
| Secretary | Yusuke Takatori(Univ. of Tokyo) / Hiroyuki Hatano(Akita Prefectural Univ.) / Takashi Shono(Okayama Univ. of Science) / Masahiro Fujii(National Defence Academy) / Shunichi Azuma(CRIEPI) / Koji Ishii(Osaka Univ.) |
| Assistant | Msataka Imao(Mitsubishi Electric) / Yanlei Gu(Ritsumeikan Univ.) / Kenshi Saho(Toyama Prefectural Univ.) / Duong Quang Thang(NAIST) / Masafumi Moriyama(NICT) / Masayuki Kinoshita(Chiba Univ. of Tech.) / SHAN LIN(NICT) / Masaki Ogura(Osaka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Intelligent Transport Systems Technology / Technical Committee on Wideband System / Technical Committee on Reliable Communication and Control |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Classification of pedestrians existing in visible or blind areas using Doppler radar |
| Sub Title (in English) | An Approach Using Long Short-Term Memory |
| Keyword(1) | Doppler Radar |
| Keyword(2) | Gait Analysis |
| Keyword(3) | Monitoring of Blind Area |
| Keyword(4) | Deep Learning |
| Keyword(5) | Long Short-Term Memory |
| 1st Author's Name | Sora Hayashi |
| 1st Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 2nd Author's Name | Daiki Isobe |
| 2nd Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| 3rd Author's Name | Kenshi saho |
| 3rd Author's Affiliation | Toyama Prefectural University(Toyama Pref. Univ.) |
| 4th Author's Name | Masao Masugi |
| 4th Author's Affiliation | Ritsumeikan University(Ritsumeikan Univ.) |
| Date | 2020-12-15 |
| Paper # | WBS2020-29,ITS2020-25,RCC2020-32 |
| Volume (vol) | vol.120 |
| Number (no) | WBS-290,ITS-291,RCC-292 |
| Page | pp.pp.121-125(WBS), pp.121-125(ITS), pp.121-125(RCC), |
| #Pages | 5 |
| Date of Issue | 2020-12-07 (WBS, ITS, RCC) |