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Paper Abstract and Keywords
Presentation 2025-02-27 13:45
Recognition of human seating posture using 3D point cloud data obtained by taking an overhead view in a desk work environment
Takumi Fukui, Hiroaki Morino (SIT) SeMI2024-88
Abstract (in Japanese) (See Japanese page) 
(in English) A possible method for detecting the seated posture of a person at a desk is to process RGB images, but capturing RGB images of the body in a real situation raises privacy concerns. In previous studies, point cloud sensors were installed in front of the target person or around the person using multiple sensors. However, it is practically difficult to install such sensors in desk work environments such as offices and schools. In this study, only one LiDAR is installed in a position where the entire measurement environment can be viewed, and the point cloud acquired by taking an overhead view is used to discriminate the seating posture. The point cloud of the object obtained by a single unit varies depending on the distance and angle from the sensor. If only the background data is simply removed, a point cloud in which a person and a chair are integrated may be obtained. To separate the two, clustering is performed in the range where the distance between the back of the chair and the back of the person is far from the back of the chair. The curvature is the ratio of eigenvalues of the covariance matrix calculated from the coordinates of the point cloud, and this was used as the feature to discriminate between a person and a chair. The result was an F value of 0.90. Then, focusing on the fact that a person adopts a seated posture depending on the inclination of the head and chest, we divided the point group discriminated as a person into head and chest, and discriminated three types of seated postures for the same person: “back straight,” “natural body,” and “stooping” using each inclination as a feature value. The result was an F value of 0.86
Keyword (in Japanese) (See Japanese page) 
(in English) LiDAR / Point Cloud data / Seating Posture / / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 384, SeMI2024-88, pp. 18-23, Feb. 2025.
Paper # SeMI2024-88 
Date of Issue 2025-02-20 (SeMI) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee SeMI IPSJ-UBI IPSJ-MBL  
Conference Date 2025-02-27 - 2025-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SeMI 
Conference Code 2025-02-SeMI-UBI-MBL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Recognition of human seating posture using 3D point cloud data obtained by taking an overhead view in a desk work environment 
Sub Title (in English)  
Keyword(1) LiDAR  
Keyword(2) Point Cloud data  
Keyword(3) Seating Posture  
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1st Author's Name Takumi Fukui  
1st Author's Affiliation Shibaura Institute of Technology (SIT)
2nd Author's Name Hiroaki Morino  
2nd Author's Affiliation Shibaura Institute of Technology (SIT)
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Speaker Author-1 
Date Time 2025-02-27 13:45:00 
Presentation Time 25 minutes 
Registration for SeMI 
Paper # SeMI2024-88 
Volume (vol) vol.124 
Number (no) no.384 
Page pp.18-23 
#Pages 6 
Date of Issue 2025-02-20 (SeMI) 

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