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| Presentation | 2019-11-06 17:30 Feature Value Extraction of Fruit Trees for Crop Estimation Using 3D Point Cloud Extended Voxel Space Analysis Kaoru Senda, Ryo Shigeta, Wei Guo, Yoshihiro Kawahara (U-Tokyo)  SeMI2019-98 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Data sensed by UAV or LiDAR remotely are utilized to extract 3D structure of plant for agriculture. For example, it is investigated and studied to estimate the volume of fruit trees based on 3D point cloud data measured by a laser scanner, e.g. LiDAR, and predict the crops using the estimated volume. Several studies have demonstrated that point cloud data can be analyzed effectively in voxel space, in which 3D space is discretized into an array of cubes called voxels. In such methods, the size of each voxel needs to be set properly. Previous studies often rely on manual parameter tuning on the size of voxels, where the relationship between volume estimation accuracy and voxel size has not been discussed enough. Therefore, this study presents an automatic voxel size adjustment, then we evaluated space resolution and calculation cost tradeoff affected by the voxel sizes. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | agriculture / LiDAR / point cloud / 3D image / voxel space / parameter tuning / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 266, SeMI2019-98, pp. 145-150, Nov. 2019. | |
| Paper # | SeMI2019-98 | |
| Date of Issue | 2019-10-29 (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 | SeMI2019-98 |
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| Conference Information | |
| Committee | SRW SeMI CNR |
| Conference Date | 2019-11-05 - 2019-11-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kozo Keisaku Engineering Inc. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IoT Workshop (Oral or Poster presentation) |
| Paper Information | |
| Registration To | SeMI |
| Conference Code | 2019-11-SRW-SeMI-CNR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Feature Value Extraction of Fruit Trees for Crop Estimation Using 3D Point Cloud Extended Voxel Space Analysis |
| Sub Title (in English) | |
| Keyword(1) | agriculture |
| Keyword(2) | LiDAR |
| Keyword(3) | point cloud |
| Keyword(4) | 3D image |
| Keyword(5) | voxel space |
| Keyword(6) | parameter tuning |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kaoru Senda |
| 1st Author's Affiliation | University of Tokyo (U-Tokyo) |
| 2nd Author's Name | Ryo Shigeta |
| 2nd Author's Affiliation | University of Tokyo (U-Tokyo) |
| 3rd Author's Name | Wei Guo |
| 3rd Author's Affiliation | University of Tokyo (U-Tokyo) |
| 4th Author's Name | Yoshihiro Kawahara |
| 4th Author's Affiliation | University of Tokyo (U-Tokyo) |
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| Speaker | Author-1 |
| Date Time | 2019-11-06 17:30:00 |
| Presentation Time | 25 minutes |
| Registration for | SeMI |
| Paper # | SeMI2019-98 |
| Volume (vol) | vol.119 |
| Number (no) | no.266 |
| Page | pp.145-150 |
| #Pages | 6 |
| Date of Issue | 2019-10-29 (SeMI) |
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