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Paper Abstract and Keywords
Presentation 2024-06-14 13:55
Quantitative Evaluation of Blind Spot Prediction using Monocular Depth Estimation and Semantic Segmentation
Takumi Tsukamoto, Koshun Hayashi, Da Li, Shintaro Ono (Fukuoka Univ.) ITS2024-3
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we propose a method for estimating and presenting blind spots on the road from monocular onboard camera images, aiming at improving the safety of vehicles, especially bicycles.
Blind spots on roads mainly appear where the depth values change discontinuously and at boundaries between objects. Focusing on these geometric characteristics, we detect blind spots by combining the edges of the depth image estimated from monocular image and the edges of the image with semantic segmentation.
In our experimental evaluation, we used a simple real image driving simulator that plays back a captured scene where a pedestrian jumps out of a blind spot, and evaluated the reaction time. The results showed that the reaction time was significantly shorter for subjects who had previously viewed a movie in which the edges of the blind spot area were highlighted.
Keyword (in Japanese) (See Japanese page) 
(in English) Driving Assistance / Traffic Safety Education / Blind Spot Prediction / Monocular Depth Estimation / Semantic Segmentation / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 79, ITS2024-3, pp. 12-16, June 2024.
Paper # ITS2024-3 
Date of Issue 2024-06-07 (ITS) 
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 ITS2024-3

Conference Information
Committee ITS  
Conference Date 2024-06-14 - 2024-06-14 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ITS 
Conference Code 2024-06-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Quantitative Evaluation of Blind Spot Prediction using Monocular Depth Estimation and Semantic Segmentation 
Sub Title (in English)  
Keyword(1) Driving Assistance  
Keyword(2) Traffic Safety Education  
Keyword(3) Blind Spot Prediction  
Keyword(4) Monocular Depth Estimation  
Keyword(5) Semantic Segmentation  
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Keyword(7)  
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1st Author's Name Takumi Tsukamoto  
1st Author's Affiliation Fukuoka University (Fukuoka Univ.)
2nd Author's Name Koshun Hayashi  
2nd Author's Affiliation Fukuoka University (Fukuoka Univ.)
3rd Author's Name Da Li  
3rd Author's Affiliation Fukuoka University (Fukuoka Univ.)
4th Author's Name Shintaro Ono  
4th Author's Affiliation Fukuoka University (Fukuoka Univ.)
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Speaker Author-4 
Date Time 2024-06-14 13:55:00 
Presentation Time 25 minutes 
Registration for ITS 
Paper # ITS2024-3 
Volume (vol) vol.124 
Number (no) no.79 
Page pp.12-16 
#Pages 5 
Date of Issue 2024-06-07 (ITS) 

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