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Structural Monitoring and Maintenance Volume 6, Number 2, June 2019 , pages 161-171 DOI: https://doi.org/10.12989/smm.2019.6.2.161 |
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Computer vision monitoring and detection for landslides |
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Tim Chen, C.F. Kuo and J.C.Y. Chen
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| Abstract | ||
| There have been a few checking frameworks intended to ensure and improve the nature of their regular habitat. The greater part of these frameworks are constrained in their capacities. In this paper, the insightful checking framework intended for debacle help and administrations has been exhibited. The ideal administrations, necessities and coming about plan proposition have been indicated. This has prompted a framework that depends fundamentally on ecological examination so as to offer consideration and security administrations to give the self-governance of indigenous habitats. In this sense, ecological acknowledgment is considered, where, in light of past work, novel commitments have been made to help include based and PC vision situations. This epic PC vision procedure utilized as notice framework for avalanche identification depends on changes in the normal landscape. The multi-criteria basic leadership strategy is used to incorporate slope data and the level of variety of the highlights. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating. | ||
| Key Words | ||
| landslide; natural disaster; feature based; computer vision; natural disasters detection; event warning system | ||
| Address | ||
| Tim Chen: Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam C.F. Kuo: Faculty of Science, Monash University, Melbourne, 3122 Victoria, Australia J.C.Y. Chen: Engineering and Decision Centre, Covenant University, 10 Idiroko Road, Canaan Land, Ota, Ogun State, Nigeria | ||
