• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.141-152
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• 2008

The 3D building modeling is one of crucial components in constructing 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes, which indeed take great amount of time and efforts. In recent years, many researches on 3D building modeling using aerial LiDAR data have been actively performed to aim at overcoming the limitations of existing 3D building modeling methods. Either techniques with interpolated grid data or data fusion with digital map and images have been investigated in most of existing researches on 3D building modeling with aerial LiDAR data. The paper proposed a method of 3D building modeling with LiDAR data only. Firstly, octree-based segmentation is applied recursively to LiDAR data classified as buildings in 3D space until there are no more LiDAR points to be segmented. Once octree-based segmentation is completed, each segmented patch is thereafter merged together based on its geometric spatial characteristics. Secondly, building model components are created with merged patches. Finally, a 3D building model is generated and composed with building model components. The experimental results with real LiDAR data showed that the proposed method was capable of modeling various types of 3D buildings.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.105-115
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• 2005

An environment model that is constructed using a single image has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the image occurs due to the occlusion. This paper introduces the registration and integration method using multiple images to resolve the above problem. This method can represent parallax effect and expand the environment model to represent wide range of environment. The segmentation-based environment modeling method using multiple images can build a detail model with optimal resolution.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.103-108
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• 2008

In case of the 3D Sketch System for spatial modeling, The use of 3D input devices in 3D environment is the best method to express designer's intention. However, the designer's 3D drawing skill is not accurate. 80, we use the multiple strokes used generally by 2D sketch. Multiple strokes make the designer recognize model's current drawing features and what he change We use the cubic-based drawing method to calculate many surfaces in real time. We arrange the relations of cubes for composing surfaces and multi strokes. We implement the sketch system taking cubic modeling and multiple strokes technique.

• The Journal of the Korea Contents Association
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• v.7 no.9
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• pp.204-211
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• 2007

In this study 3D topographic modeling was made by using aerial photography and digital terrain map, through this we did visibility analysis and implemented Web GIS of Dong-A university. Studying area was Busan Saha-gu Hadan-dong, we used aerial photography on a scale of 1:20,000 and digital terrain map on a scale of 1:5,000. Ortho correction image was made by aerial photography through selecting GCP, image matching, image resampling and precise differential rectification. And DEM on digital map was created using ArcView program, making 3D topographic modeling by road layer and building layer and implementing Web GIS about Dong-A university.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.323-324
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• 2013

본 논문에서는 2차원 X-ray 영상을 이용하여 3차원 영상을 얻기 위한 전처리 과정으로 2차원 X-ray 영상에서 원하는 뼈 영상을 분할하기 위한 능동적 대퇴골 분할 기법에 대해 제안하고 구현하였다. X-ray 영상의 주된 화질 저하 요인인 잡음을 제거하고 에지 및 밝기 검출을 통하여 정확하고 빠른 뼈 영상 분할 기법을 구현하였고 대퇴골 영상을 통해 검증하였다. 이를 통해 최소한의 2차원 X-ray 영상을 이용하여 3차원 뼈 모델링을 구현하는데 필요한 뼈 영상을 획득하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.573-576
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• 2022

본 논문에서는 삼각형 구조로 구성된 3차원 메쉬(Mesh)에서 합성곱 신경망(Convolutional Neural Network, CNN)의 정확도를 개선시킬 수 있는 새로운 학습 표현 기법을 제시한다. 우리는 메쉬를 구성하고 있는 삼각형의 넓이와 그 로컬 특징을 기반으로 학습을 진행한다. 일반적으로 딥러닝은 인공신경망을 수많은 계층 형태로 연결한 기법을 말하며, 주요 처리 대상은 오디오 파일과 이미지이었다. 인공지능에 대한 연구가 지속되면서 3차원 딥러닝이 도입되었지만, 기존의 학습과는 달리 3차원 학습은 데이터의 확보가 쉽지 않다. 혼합현실과 메타버스 시장으로 인해 3차원 모델링 시장이 증가가 하면서 기술의 발전으로 데이터를 획득할 수 있는 방법이 생겼지만, 3차원 데이터를 직접적으로 학습 표현하는 방식으로 적용하는 것은 쉽지 않다. 그렇기 때문에 본 논문에서는 산업 현장에서 사용되는 데이터인 삼각형 메쉬 구조를 바탕으로 기존 방법보다 정확도가 높은 학습 기법을 제안한다.

• Journal of the Korean GEO-environmental Society
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• v.12 no.7
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• pp.57-65
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• 2011

Numerical simulations by three-dimensional Particle Flow Code($PFC^{3D}$, Itasca) considering distinct element method (DEM) were carried out for prediction of triaxial compression test with sand material. The effect of scale conditions for numerical model and distinct material on final prediction results was analyzed by numerical models under various scale conditions, and following observations were made from the numerical experiments. It is very useful to model the initial material condition without any porosity conversion from 2-D to 3-D DEM. Numerical experiments have shown that in all cases considered, 3D distinct element modeling could provide good agreement on stress-strain behavior, volume change and strength properties with laboratory testing results. It was important thing to assess reasonable scale ratio of numerical model and distinct elements for saving calculation time and securing calculation efficiency under condition with accuracy and appropriateness as numerical laboratory. As results of DEM simulations under various scale conditions, most of results show that shear strength properties as cohesion and internal friction angle are similar in condition of $D_{mod}/D_{gmax}$ < 10. It shows that 3-D distinct element method could be used as efficient tool to assess strength properties by numerical laboratory technique.

• Economic and Environmental Geology
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• v.27 no.2
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• pp.191-199
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• 1994

We have developed an algorithm based on the method of integral equations to simulate the magnetotelluric (MT) responses of three-dimensional (3-D) bodies in a layered half-space. The inhomogeneities are divided into a number of cells and are replaced by an equivalent current distribution which is approximated by pulse basis functions. A matrix equation is constructed using the electric Green's tensor function appropriate to a layered earth, and is solved for the vector current in each cell. Subsequently, scattered fields are found by integrating electric and magnetic Green's tensor functions over the scattering current About a 3-D conductive body near the earth's surface, interpretation using 2-D transverse electric modeling schemes can imply highly erratic low resistivities at depth. This is why these routines do not account for the effect of boundary charges. However, centrally located profiles across elongate 3-D prisms may be modeled accurately with a 2-D transverse magnetic algorithm, which implicitly includes boundary charges in its formulation. Multifrequency calculations show that apparent resistivity and impedance phase are really two complementary parameters. Hence, they should be treated simultaneously in broadband MT interpretation.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.663-670
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• 2016

This paper proposes the 3D-modeling-based image template matching method. It is more convenient than contemporary 2D-template-based methods that use many 2D image templates for possible angles and sizes in matching process.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.25-32
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• 2005

This paper presents a method for point-based 3D building reconstruction using Lidar data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression) in the first place. If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LIDAR data and digital map could be a feasible method of modeling 3D building reconstruction.