• Journal of the Korea Computer Graphics Society
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• v.22 no.2
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• pp.1-10
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• 2016

The computational cost of clothing simulation and rendering is mainly depends on the type of mesh and its quality. Thus, quadrilateral meshes are generally preferred over triangular meshes for the reasons of accuracy and efficiency. This paper presents a method of quadrangulating sewing pattern based on the recursive geometry decomposition method. Herein, we proposed two simple improvements to the previous algorithms. The first one deals with the recursive geometry decomposition in which the physical domain is decomposed into simple and mappable regions. The second proposed algorithm deals with the vertex validation in which the invalid vertex classification can be validated.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.184-186
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• 2003

본 논문에서는 대규모 지형 데이터를 이용한 네트웍 환경에서의 지형 탐색을 위한 다중 해상도 기법과 prefetching 기법을 제안한다. 지형 렌더링에 널리 사용되는 직각이등변 삼각형 메쉬 형태의 DEM 데이터를 정삼각형 메친 데이터로 재구성한 뒤, 이를 다중 해상도로 구조화하여. 네트웍 환경에서의 주요 문제점인 대역폭과 지연 문제를 보완하였다. 본 기법은 3차원 지형 데이터를 이용한 온라인 게임 등에 응용될 수 있다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.