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Near-real-time gradually expanding 3D land surface reconstruction in disaster areas by sequential drone imagery
https://nied-repo.bosai.go.jp/records/2777
https://nied-repo.bosai.go.jp/records/2777f3eb3c49-3d42-4d2c-a57f-473606c604a1
| Item type | researchmap(1) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2023-03-30 | |||||||||||||
| タイトル | ||||||||||||||
| 言語 | en | |||||||||||||
| タイトル | Near-real-time gradually expanding 3D land surface reconstruction in disaster areas by sequential drone imagery | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| 著者 |
Min-Lung Cheng
× Min-Lung Cheng
× Masashi Matsuoka
× Wen Liu
× Fumio Yamazaki
|
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Other | |||||||||||||
| 内容記述 | The ability of drones to access disaster areas has been proven powerful and flexible for acquiring first-hand optical imagery data for environmental observation. However, such imagery data usually undergo postprocessing, and the three-dimensional (3D) products are mainly for accurate land surveys. The postprocessing procedure is too time-consuming to meet instant decision support and rescue response requirements. Therefore, this paper intends to develop a systematic workflow that is able to achieve on-the-fly 3D reconstruction in disaster areas by optical imagery sequentially acquired by drones. This study proposes a strategy to spatially link sequential images (SLSI) for image localization and suitable stereopair selection. In addition, the criteria for valid epipolar stereoapair determination are developed to make the 3D dense reconstruction more automatic and effective. The 3D digital land surface can be gradually reconstructed and expanded in the computer system while the drone is capturing new images. This paper utilizes the imagery dataset of collapsed buildings induced by the 2016 Kumamoto earthquake in Japan to simulate the more effective 3D reconstruction. Although the accuracy of the consequence is reported to be closely one meter, the mean data processing time for every image can achieve the level by approximately ten seconds while performing the proposed scheme on an iMac with Intel Core i5 and 16 GB random access memory (RAM). As a result, the efficiency and computational power needed are significantly reduced to support emergency applications soon after a disaster occurs. | |||||||||||||
| 言語 | en | |||||||||||||
| 書誌情報 |
en : Automation in Construction 巻 135, p. 104105-104105, 発行日 2022-03 |
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| 出版者 | ||||||||||||||
| 言語 | en | |||||||||||||
| 出版者 | Elsevier BV | |||||||||||||
| ISSN | ||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||
| 収録物識別子 | 0926-5805 | |||||||||||||
| DOI | ||||||||||||||
| 関連識別子 | 10.1016/j.autcon.2021.104105 | |||||||||||||
