University of Oulu

H. N. Vu et al., "Landslide Detection with Unmanned Aerial Vehicles," 2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR), Hanoi, Vietnam, 2021, pp. 1-7, doi: 10.1109/MAPR53640.2021.9585261

Landslide detection with unmanned aerial vehicles

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Author: Vu, Hoai Nam1; Nguyen, Huong Mai2; Pham, Cuong Duc3;
Organizations: 1Naver AI Lab Posts and Telecommunications, Institute of Technology, Ha Noi, Viet Nam
2University of Oulu Oulu, Finland
3IVS Technology, Ha Noi, Viet Nam
4Posts and Telecommunications, Institute of Technology, Hanoi, Vietnam
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: IEEE, 2021
Publish Date: 2023-03-23


Landslide is one of the most dangerous disasters, especially for countries with large mountainous terrain. It causes a great damage to lives, infrastructure and environments, such as traffic congestion and high accidents. Therefore, automated landslide detection is an important task for warning and reducing its consequences such as blocked traffic or traffic accidents. For instance, people approaching the disaster area can adjust their routes to avoid blocked roads, or dangerous traffic signs can be positioned in time to warn the traffic participants to avoid the interrupted road ahead. This paper proposes a method to detect blocked roads caused by landslide by utilizing images captured from Unmanned Aerial Vehicles (UAV). The proposed method comprises of three components: road segmentation, blocked road candidate extraction, and blocked road classification, which is leveraged by a multi-stage convolutional neural network model. Our experiments demonstrate that the proposed method can surpass over several state-of-the art methods on our self-collected dataset of 400 images captured with an UAV.

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ISBN: 978-1-6654-1910-9
ISBN Print: 978-1-6654-1911-6
Pages: 1 - 7
Article number: 9585261
DOI: 10.1109/MAPR53640.2021.9585261
Host publication: 2021 International Conference on Multimedia Analysis and Pattern Recognition (MAPR)
Conference: International Conference on Multimedia Analysis and Pattern Recognition
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: Hoai Nam Vu was funded by Vingroup Joint Stock Company and supported by the Domestic Master/ PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VINBIGDATA), code VINIF.2020.TS.103.
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