| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2023-02-23 |
| タイトル |
|
|
タイトル |
Model Scaling in Smartphone GNSS-Aided Photogrammetry for Fragmentation Size Distribution Estimation |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
point cloud scaling |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
fragmentation size analysis |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
structure from motion |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 作成者 |
Tungol, ZedrickPaulL.
Toriya, Hisatoshi
Owada, Narihiro
Kitahara, Itaru
Inagaki, Fumiaki
Saadat, Mahdi
Jang, HyongDoo
Kawamura, Youhei
|
| 内容記述 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Fragmentation size distribution estimation is a critical process in mining operations that employ blasting. In this study, we aim to create a low-cost, efficient system for producing a scaled 3D model without the use of ground truth data, such as GCPs (Ground Control Points), for the purpose of improving fragmentation size distribution measurement using GNSS (Global Navigation Satellite System)-aided photogrammetry. However, the inherent error of GNSS data inhibits a straight-forward application in Structure-from-Motion (SfM). To overcome this, the study proposes that, by increasing the number of photos used in the SfM process, the scale error brought about by the GNSS error will proportionally decrease. Experiments indicated that constraining camera positions to locations, relative or otherwise, improved the accuracy of the generated 3D model. In further experiments, the results showed that the scale error decreased when more images from the same dataset were used. The proposed method is practical and easy to transport as it only requires a smartphone and, optionally, a separate camera. In conclusion, with some modifications to the workflow, technique, and equipment, a muckpile can be accurately recreated in scale in the digital world with the use of positional data. |
|
言語 |
en |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 書誌情報 |
en : MINERALS
巻 11,
号 12,
発行日 2021
|
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2075-163X |
| 出版者 |
|
|
出版者 |
MDPI |
|
言語 |
en |
| 関連情報 |
|
|
関連タイプ |
isIdenticalTo |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.3390/min11121301 |
| 権利情報 |
|
|
権利情報 |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
kokuA_2022_15.pdf (66.9 MB)
