| Item type |
SIG Technical Reports(1) |
| 公開日 |
2022-05-19 |
| タイトル |
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|
タイトル |
Human Identification Based On Point Cloud Captured By Small-Size LiDAR |
| タイトル |
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言語 |
en |
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タイトル |
Human Identification Based On Point Cloud Captured By Small-Size LiDAR |
| 言語 |
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|
言語 |
eng |
| キーワード |
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主題Scheme |
Other |
|
主題 |
空間情報処理 |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_18gh |
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資源タイプ |
technical report |
| 著者所属 |
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者所属 |
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者所属 |
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者所属(英) |
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en |
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者所属(英) |
|
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en |
|
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者所属(英) |
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|
en |
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Grad. Sch. of Info. Sci. and Tech., Osaka University |
| 著者名 |
Shota, Yamada
Rizk, Hamada
Hirozumi, Yamaguchi
|
| 著者名(英) |
Shota, Yamada
Rizk, Hamada
Hirozumi, Yamaguchi
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| 論文抄録 |
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内容記述タイプ |
Other |
|
内容記述 |
The demand for safety-enhancing solutions is on the rise, especially due to COVID-19's rapid spread. In order to track infected cases and hence restrict the spread of the virus, real-time life-logging is an essential application. This application highlights the necessity for a precise human identification technique in situations when cameras are not feasible owing to privacy concerns. The potential of the LiDAR sensor to represent the surrounding world in the form of a 3D point cloud has recently gained interest. In this paper, we present a new wearable device with a small-sized LiDAR that may be used to create an onboard human identification system for life-logging. Our proposed system starts with clustering to remove noise and background. Then fisher features are extracted from them. After that, the collected characteristics are utilized to train classifiers to identify the subjects. We conducted two different experiments to evaluate the suggested system. We collected six and thirteen subjects for each experiment. The results show that the proposed system can effectively remove noise and accurately identify subjects with at least 95% accuracy in both experiments. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The demand for safety-enhancing solutions is on the rise, especially due to COVID-19's rapid spread. In order to track infected cases and hence restrict the spread of the virus, real-time life-logging is an essential application. This application highlights the necessity for a precise human identification technique in situations when cameras are not feasible owing to privacy concerns. The potential of the LiDAR sensor to represent the surrounding world in the form of a 3D point cloud has recently gained interest. In this paper, we present a new wearable device with a small-sized LiDAR that may be used to create an onboard human identification system for life-logging. Our proposed system starts with clustering to remove noise and background. Then fisher features are extracted from them. After that, the collected characteristics are utilized to train classifiers to identify the subjects. We conducted two different experiments to evaluate the suggested system. We collected six and thirteen subjects for each experiment. The results show that the proposed system can effectively remove noise and accurately identify subjects with at least 95% accuracy in both experiments. |
| 書誌レコードID |
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収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA11851388 |
| 書誌情報 |
研究報告モバイルコンピューティングと新社会システム（MBL）
巻 2022-MBL-103,
号 38,
p. 1-8,
発行日 2022-05-19
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| ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
2188-8817 |
| Notice |
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SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. |
| 出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |
IPSJ-MBL22103038.pdf (21.4 MB)
