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 2022-03-08 14:45
Evaluation of Data Augmentation Methods Considering Occlusion Region for 3D Point Cloud Classification
Shiori Maki, Kenji Kanai, Shota Hirose, Heming Sun, Jiro Katto (Waseda Univ.) SeMI2021-91
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, research of point cloud classification using deep learning has been improved. In this paper, we propose a data augmentation method for building a robust model against occlusions. The proposed model is inspired by the 2D data augmentation methods, such as random erasing and cutout methods. Through the performance evaluations, we verify that the proposed method can contribute to improvement of classification accuracy even if a part of point cloud is lacked due to the occlusion. In addition, we also verify availability of the proposed method against real data and adversarial data that intentionally drops important points.
Keyword (in Japanese) (See Japanese page) 
(in English) Point Cloud / Deep Learning / Data Augmentation / Digital Twin / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 411, SeMI2021-91, pp. 47-52, March 2022.
Paper # SeMI2021-91 
Date of Issue 2022-02-28 (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)
Download PDF SeMI2021-91

Conference Information
Committee SeMI IPSJ-MBL IPSJ-UBI  
Conference Date 2022-03-07 - 2022-03-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SeMI 
Conference Code 2022-03-SeMI-MBL-UBI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of Data Augmentation Methods Considering Occlusion Region for 3D Point Cloud Classification 
Sub Title (in English)  
Keyword(1) Point Cloud  
Keyword(2) Deep Learning  
Keyword(3) Data Augmentation  
Keyword(4) Digital Twin  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shiori Maki  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Kenji Kanai  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Shota Hirose  
3rd Author's Affiliation Waseda University (Waseda Univ.)
4th Author's Name Heming Sun  
4th Author's Affiliation Waseda University (Waseda Univ.)
5th Author's Name Jiro Katto  
5th Author's Affiliation Waseda University (Waseda Univ.)
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 Author-1 
Date Time 2022-03-08 14:45:00 
Presentation Time 25 minutes 
Registration for SeMI 
Paper # SeMI2021-91 
Volume (vol) vol.121 
Number (no) no.411 
Page pp.47-52 
#Pages
Date of Issue 2022-02-28 (SeMI) 


[Return to Top Page]

[Return to IEICE Web Page]


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