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Paper Abstract and Keywords
Presentation 2021-03-03 09:20
Study of Environment Recognition and 3D Map Generation Using SegNet for Night Forest Monitoring Using an Environmental Monitoring Robot
Takeo Kaneko (WASEDA Univ.), Junji Yamato (Kogakuin Univ.), Hiroyuki Ishii, Jun Ohya, Atuo Takanishi (WASEDA Univ.) IMQ2020-29 IE2020-69 MVE2020-61
Abstract (in Japanese) (See Japanese page) 
(in English) Towards the actualization of autonomous robots that monitor forests, around which various kinds of damages caused by wild animals frequently occur, this paper proposes a method for obtaining 3D maps based on labeled image segmentation results at night. The cameras mounted on the monitoring robot acquires IR (infrared) images and depth images. To the acquired images, CNN (Convolutional Neural Network) is performed so that the segmentation result of the IR image is obtained. Then, by registering the 3D point cloud obtained from the depth image to the segmentation result, a labeled 3D map is obtained. Experiments that evaluate the proposed method using IR images and depth images acquired in forests at night were conducted. It turns out that accurate segmentation results and labeled 3D maps are obtained.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / SegNet / Point Cloud / 3D Map / IR image / SLAM / OctoMap /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 390, IE2020-69, pp. 91-96, March 2021.
Paper # IE2020-69 
Date of Issue 2021-02-22 (IMQ, IE, MVE) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 IMQ2020-29 IE2020-69 MVE2020-61

Conference Information
Committee MVE IMQ IE CQ  
Conference Date 2021-03-01 - 2021-03-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2021-03-MVE-IMQ-IE-CQ 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study of Environment Recognition and 3D Map Generation Using SegNet for Night Forest Monitoring Using an Environmental Monitoring Robot 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) SegNet  
Keyword(3) Point Cloud  
Keyword(4) 3D Map  
Keyword(5) IR image  
Keyword(6) SLAM  
Keyword(7) OctoMap  
1st Author's Name Takeo Kaneko  
1st Author's Affiliation Waseda University (WASEDA Univ.)
2nd Author's Name Junji Yamato  
2nd Author's Affiliation Kogakuin University (Kogakuin Univ.)
3rd Author's Name Hiroyuki Ishii  
3rd Author's Affiliation Waseda University (WASEDA Univ.)
4th Author's Name Jun Ohya  
4th Author's Affiliation Waseda University (WASEDA Univ.)
5th Author's Name Atuo Takanishi  
5th Author's Affiliation Waseda University (WASEDA Univ.)
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Speaker Author-1 
Date Time 2021-03-03 09:20:00 
Presentation Time 25 minutes 
Registration for IE 
Paper # IMQ2020-29, IE2020-69, MVE2020-61 
Volume (vol) vol.120 
Number (no) no.389(IMQ), no.390(IE), no.391(MVE) 
Page pp.91-96 
Date of Issue 2021-02-22 (IMQ, IE, MVE) 

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