| Presentation | 2022-09-13 Video Anomaly Detection Method using Deep Learning Models and Crowd Workers Ryuya Itano, Tomoya Nohara, Takahiro Koita, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, the number of surveillance cameras installed has been increasing due to the spread of IoT. However, this does not mean an increase in manpower to detect anomalies from surveillance camera images. Although several methods using deep learning have been investigated to automate anomaly detection, they have not achieved sufficient detection accuracy. A method using crowdsourcing that incorporates the advanced cognitive abilities of human crowd workers can improve detection accuracy, but incurs a cost for the crowdworkers. In this study, we propose a new video anomaly detection method that combines high accuracy and low cost through the cooperation of deep learning and crowd workers. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Anomaly Detection / Human-in-the-loop / Crowdsourcing |
| Paper # | LOIS2022-10,IE2022-32,EMM2022-38 |
| Date of Issue | 2022-09-06 (LOIS, IE, EMM) |
| Conference Information | |
| Committee | ITE-ME / EMM / IE / LOIS / IEE-CMN / IPSJ-AVM |
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| Conference Date | 2022/9/13(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Keio Univ. Yagami Campus (Hybrid) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | / Ryoichi Nishimura(NICT) / Kazuya Kodama(NII) / Hiroyuki Toda(NTT) / Shun Morimura(CRIEPI) / Hiroyuki Kasai(Waseda University) |
| Vice Chair | / Kotaro Sonoda(Nagasaki Univ.) / Masatsugu Ichino(Univ. of Electro-Comm.) / Hiroyuki Bandoh(NTT) / Toshihiko Yamazaki(Univ. of Tokyo) / Manabu Motegi(Takushoku Univ.) / Kouji Hirata(Kansai Univ) |
| Secretary | / Kotaro Sonoda(Kaishi Professional Univ.) / Masatsugu Ichino(Chiba Univ.) / Hiroyuki Bandoh(KDDI Research) / Toshihiko Yamazaki(Nagoya Inst. of Tech.) / Manabu Motegi(Nagasaki Univ.) / Kouji Hirata(NTT) / (Tokai Univ.) |
| Assistant | / Tomoko Kajiyama(Hiroshima City Univ.) / Shieyuki Sakazawa(Osaka Inst. of Tech.) / Shunsuke Iwamura(NHK) / Shinobu Kudo(NTT) / Mana Sasagawa(NTT) / Yuuichi Shinohara(TEPCO Power Grid) / Akihiro Tanaka(CRIEPI) |
| Paper Information | |
| Registration To | Technical Group on Media Engineering / Technical Committee on Enriched MultiMedia / Technical Committee on Image Engineering / Technical Committee on Life Intelligence and Office Information Systems / Technical Meeting on Communications / Special Interest Group on Audio Visual and Multimedia Information Processing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Video Anomaly Detection Method using Deep Learning Models and Crowd Workers |
| Sub Title (in English) | |
| Keyword(1) | Anomaly Detection |
| Keyword(2) | Human-in-the-loop |
| Keyword(3) | Crowdsourcing |
| 1st Author's Name | Ryuya Itano |
| 1st Author's Affiliation | Graduate School of Doshisha University(Doshisha Univ.) |
| 2nd Author's Name | Tomoya Nohara |
| 2nd Author's Affiliation | Doshisha University(Doshisha Univ.) |
| 3rd Author's Name | Takahiro Koita |
| 3rd Author's Affiliation | Graduate School of Doshisha University(Doshisha Univ.) |
| Date | 2022-09-13 |
| Paper # | LOIS2022-10,IE2022-32,EMM2022-38 |
| Volume (vol) | vol.122 |
| Number (no) | LOIS-177,IE-178,EMM-179 |
| Page | pp.pp.1-6(LOIS), pp.1-6(IE), pp.1-6(EMM), |
| #Pages | 6 |
| Date of Issue | 2022-09-06 (LOIS, IE, EMM) |