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| 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 |
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| 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 | 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 | IMQ2020-29 IE2020-69 MVE2020-61 |
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| 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 |
| Keyword(8) | |
| 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 |
| #Pages | 6 |
| Date of Issue | 2021-02-22 (IMQ, IE, MVE) |
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