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Hokkaido University Collection of Scholarly and Academic Papers >
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Model Scaling in Smartphone GNSS-Aided Photogrammetry for Fragmentation Size Distribution Estimation
| Title: | Model Scaling in Smartphone GNSS-Aided Photogrammetry for Fragmentation Size Distribution Estimation |
| Authors: | Tungol, Zedrick Paul L. Browse this author | | Toriya, Hisatoshi Browse this author | | Owada, Narihiro Browse this author | | Kitahara, Itaru Browse this author | | Inagaki, Fumiaki Browse this author | | Saadat, Mahdi Browse this author | | Jang, Hyong Doo Browse this author | | Kawamura, Youhei Browse this author →KAKEN DB |
| Keywords: | point cloud scaling | | fragmentation size analysis | | structure from motion |
| Issue Date: | Dec-2021 |
| Publisher: | MDPI |
| Journal Title: | Minerals |
| Volume: | 11 |
| Issue: | 12 |
| Start Page: | 1301 |
| Publisher DOI: | 10.3390/min11121301 |
| Abstract: | 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. |
| Rights: | © 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 License (http://creativecommons.org/licenses/by/4.0/). |
| Type: | article |
| URI: | http://hdl.handle.net/2115/83891 |
| Appears in Collections: | 工学院・工学研究院 (Graduate School of Engineering / Faculty of Engineering) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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