IEICE Technical Committee Submission System
Conference Paper's Information
Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2021-03-05 15:40
An approach for predicting traffic accidents at intersections with 360 degree panorama images
Daiki Tanaka, Kiyoharu Aizawa (The Univ. of Tokyo) PRMU2020-97
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we used deep learning to predict traffic accidents. Traffic accidents are caused by a complex combination of various factors, and it is physically difficult to collect detailed data for each location. We investigated a new problem setting of determining whether a traffic accident occurs in the future using only a single 360 degree image of each location. Experimental results demonstrate that a deep neural network can predict traffic accident locations with an accuracy of more than 78%.
Keyword (in Japanese) (See Japanese page) 
(in English) 360 degree panorama images / Deep learning / Traffic accident prediction / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 409, PRMU2020-97, pp. 158-163, March 2021.
Paper # PRMU2020-97 
Date of Issue 2021-02-25 (PRMU) 
ISSN Print edition: ISSN 0913-5685  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 PRMU2020-97

Conference Information
Committee PRMU IPSJ-CVIM  
Conference Date 2021-03-04 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computer Vision and Pattern Recognition for specific environment 
Paper Information
Registration To PRMU 
Conference Code 2021-03-PRMU-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An approach for predicting traffic accidents at intersections with 360 degree panorama images 
Sub Title (in English)  
Keyword(1) 360 degree panorama images  
Keyword(2) Deep learning  
Keyword(3) Traffic accident prediction  
Keyword(4)  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Daiki Tanaka  
1st Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
2nd Author's Name Kiyoharu Aizawa  
2nd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
3rd Author's Name  
3rd Author's Affiliation ()
4th Author's Name  
4th Author's Affiliation ()
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
Speaker
Date Time 2021-03-05 15:40:00 
Presentation Time 15 
Registration for PRMU 
Paper # IEICE-PRMU2020-97 
Volume (vol) IEICE-120 
Number (no) no.409 
Page pp.158-163 
#Pages IEICE-6 
Date of Issue IEICE-PRMU-2021-02-25 


[Return to Top Page]

[Return to IEICE Web Page]


The Institute of Electronics, Information and Communication Engineers (IEICE), Japan