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User Identification Method based on Head Shape Using Pressure Sensors Embedded in a Helmet
https://ipsj.ixsq.nii.ac.jp/records/213300
https://ipsj.ixsq.nii.ac.jp/records/21330096fa4dde-72a4-4816-b7b1-01f27e16be40
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-JNL6210005.pdf (2.7 MB)
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Copyright (c) 2021 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||
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| 公開日 | 2021-10-15 | |||||||||
| タイトル | ||||||||||
| タイトル | User Identification Method based on Head Shape Using Pressure Sensors Embedded in a Helmet | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | User Identification Method based on Head Shape Using Pressure Sensors Embedded in a Helmet | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | [特集：ユビキタスコンピューティングシステム（X）] User identification, pressure sensor, helmet, head shape | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Ritsumeikan University | ||||||||||
| 著者所属 | ||||||||||
| Ritsumeikan University／PRESTO, Japan Science and Technology Agency | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Ritsumeikan University | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Ritsumeikan University / PRESTO, Japan Science and Technology Agency | ||||||||||
| 著者名 |
Atsuhiro, Fujii
× Atsuhiro, Fujii
× Kazuya, Murao
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| 著者名(英) |
Atsuhiro, Fujii
× Atsuhiro, Fujii
× Kazuya, Murao
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Various types of helmets exist, including industrial protective helmets, motorcycle helmets, sports helmets, and military/police helmets. By identifying individuals wearing a helmet, their name, affiliation, and qualification can be presented on a display mounted on the helmet, and sensor data collected through the helmet, such as acceleration, video, and eye-tracking data, can be labeled with the user's ID. In this paper, we propose a user identification method based on head shape using a helmet equipped with 32 pressure sensors. Our method has two functions: user identification and authentication. User identification is based on the assumption that a single helmet is shared by multiple individuals. The goal of this method is to identify which of the registered people is the person wearing the helmet. User authentication determines whether the individual wearing the helmet is the individual with the ID when the ID is provided to the system. In the evaluation, we obtained sensor values for 2 seconds 20 times from nine subjects as head shape data. The accuracy was evaluated using 5-fold cross-validation, and we achieved 100% accuracy with five sensors and 92% with two sensors for user identification and an average equal error rate of 0.076 with 32 sensors for user authentication. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.29(2021) (online) DOI http://dx.doi.org/10.2197/ipsjjip.29.610 ------------------------------ |
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| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | Various types of helmets exist, including industrial protective helmets, motorcycle helmets, sports helmets, and military/police helmets. By identifying individuals wearing a helmet, their name, affiliation, and qualification can be presented on a display mounted on the helmet, and sensor data collected through the helmet, such as acceleration, video, and eye-tracking data, can be labeled with the user's ID. In this paper, we propose a user identification method based on head shape using a helmet equipped with 32 pressure sensors. Our method has two functions: user identification and authentication. User identification is based on the assumption that a single helmet is shared by multiple individuals. The goal of this method is to identify which of the registered people is the person wearing the helmet. User authentication determines whether the individual wearing the helmet is the individual with the ID when the ID is provided to the system. In the evaluation, we obtained sensor values for 2 seconds 20 times from nine subjects as head shape data. The accuracy was evaluated using 5-fold cross-validation, and we achieved 100% accuracy with five sensors and 92% with two sensors for user identification and an average equal error rate of 0.076 with 32 sensors for user authentication. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.29(2021) (online) DOI http://dx.doi.org/10.2197/ipsjjip.29.610 ------------------------------ |
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| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00116647 | |||||||||
| 書誌情報 |
情報処理学会論文誌 巻 62, 号 10, 発行日 2021-10-15 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7764 | |||||||||
