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Paper Abstract and Keywords
Presentation 2024-12-05 13:30
A Study on the Detection of Pedestrians Reflected on Painted Surfaces
Rei Oyama, Yusuke Takatori (Kanagawa Inst of Tec) WBS2024-62 ITS2024-43 RCC2024-67
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, a method for detecting pedestrians located outside the vehicle's line of sight by using deep learning-based object detection on images reflected on painted surfaces, such as the sides of other vehicles is proposed. As an object detection method, we applied an existing general-purpose object detection model, which was trained on images of people directly captured, to painted surface reflection images. However, due to insufficient detection accuracy, we have constructed a model specifically trained on painted surface reflection images. The model was trained on images reflected on painted surfaces, but it was found that there was a lack of data variation and that constructing a model tailored to the paint color was necessary to improve accuracy. Therefore, we generated images that mimicked human images reflected on reflective surfaces based on directly photographed human images, constructed a learning model, and evaluated it using actual painted reflective surface images. As a result of evaluating the learning model constructed with a total of 2,000 generated images, people could be detected with 90% accuracy. This shows that the learning model of processed images (pseudo painted reflection images) is effective for objects reflected on painted reflective surfaces.
Keyword (in Japanese) (See Japanese page) 
(in English) ITS / NLOS obstacle position estimation / Pedestrian detection / Deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 284, ITS2024-43, pp. 175-180, Dec. 2024.
Paper # ITS2024-43 
Date of Issue 2024-11-27 (WBS, ITS, RCC) 
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)
Download PDF WBS2024-62 ITS2024-43 RCC2024-67

Conference Information
Committee WBS ITS RCC  
Conference Date 2024-12-04 - 2024-12-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Kagoshima Prefectural Culture Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ITS 
Conference Code 2024-12-WBS-ITS-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on the Detection of Pedestrians Reflected on Painted Surfaces 
Sub Title (in English)  
Keyword(1) ITS  
Keyword(2) NLOS obstacle position estimation  
Keyword(3) Pedestrian detection  
Keyword(4) Deep learning  
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1st Author's Name Rei Oyama  
1st Author's Affiliation Kanagawa Institute of Technology (Kanagawa Inst of Tec)
2nd Author's Name Yusuke Takatori  
2nd Author's Affiliation Kanagawa Institute of Technology (Kanagawa Inst of Tec)
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Speaker Author-1 
Date Time 2024-12-05 13:30:00 
Presentation Time 25 minutes 
Registration for ITS 
Paper # WBS2024-62, ITS2024-43, RCC2024-67 
Volume (vol) vol.124 
Number (no) no.283(WBS), no.284(ITS), no.285(RCC) 
Page pp.175-180 
#Pages 6 
Date of Issue 2024-11-27 (WBS, ITS, RCC) 

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