• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.77-85
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• 1997

Researches in the field of Computer Graphics and Geographical Information Systems(GIS) have extensively studied the method of photo-realistic landscape modelling, because it have become a commom requirement in applications such as flight simulators, mission rehearsal, and construction planning. A common approach to the display of terrain uses a Digital Elevation Model(DEM). DEM is an evenly spaced array of the terrain elevation data and can be obtained from stereo satellite data. With the DEM data, the process of 3D terrain modelling consists of three steps. The first step is to extract the meaningful data (such as peak, pit, passes...) from DEM data based on LOD(Level Of Detail) criteria. The second is to construct the 3D surface by TIN, which represents a surface as a set of non-overlapping continuous triangular facets of irregular size and shape. The third is a rendering of 3D terrain model. The goal of this research is a construction of 3D terrain with TIN. To do this, we are going to app]y Radial Sweep Algorithm. Radial Sweep Algorithm for generating TIN works quickly and efficiently. However, it does not solve the problem caused by the approximated nature of triangulated surface. To solve this problem, this research derive improved radial sweep algorithms with the optimal triangle definition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.233-240
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• 2000

We designed a 3D solid modeler based on the web, which was independent from platforms, which could be executed without 3D graphics softwares. In this paper, we show the design of system libraries and how to implement in Java 3D. A client connects to the solid modeler server, design solid model, stores the data as the various file format, and displays the data from other CAD systems. This solid modeler can support the detail design as 3D graphics features such as viewing, rendering, animating are available.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.33-43
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• 2020

Retrieving a 3D model from a 3D database and augmenting the retrieved model in the Augmented Reality system simultaneously became an issue in developing the plausible AR environments in a convenient fashion. It is considered that the sketch-based 3D object retrieval is an intuitive way for searching 3D objects based on human-drawn sketches as query. In this paper, we propose a novel deep learning based approach of retrieving a sketch-based 3D object as for an Augmented Reality Model. For this work, we introduce a new method which uses Sketch CNN, Wasserstein CNN and Wasserstein center loss for retrieving a sketch-based 3D object. Especially, Wasserstein center loss is used for learning the center of each object category and reducing the Wasserstein distance between center and features of the same category. The proposed 3D object retrieval and augmentation consist of three major steps as follows. Firstly, Wasserstein CNN extracts 2D images taken from various directions of 3D object using CNN, and extracts features of 3D data by computing the Wasserstein barycenters of features of each image. Secondly, the features of the sketch are extracted using a separate Sketch CNN. Finally, we adopt sketch-based object matching method to localize the natural marker of the images to register a 3D virtual object in AR system. Using the detected marker, the retrieved 3D virtual object is augmented in AR system automatically. By the experiments, we prove that the proposed method is efficiency for retrieving and augmenting objects.

• Journal of Integrative Natural Science
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• v.5 no.1
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• pp.6-12
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• 2012

c-Jun N-terminal kinase-3 (JNK-3) has been identified as a promising target for neuronal apoptosis and has the effective therapeutic for neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, and other CNS disorders. Herein, we report the essential structural and chemical parameters for JNK-3 inhibitors utilizing comparative molecular field similarity indices analysis (CoMSIA) using the derivatives of 3,5-disubstituted quinolines. The best predictions were obtained CoMSIA model (q2=0.834, r2=0.987) and the statistical parameters from the generated 3D-QSAR models were indicated that the data are well fitted and have high predictive ability. The resulting contour map from 3D-QSAR models might be helpful to design novel and more potent JNK3 derivatives.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.121-130
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• 2011

This paper highlights the reconstruction of the rectilinear type of 3D rooftop model from satellite image data using centroid neural network. The main idea of the proposed 3D reconstruction method is based on the grouping of 3D line segments. 3D lines are extracted by 2D lines and DEM (Digital Elevation Map) data evaluated from a pair of stereo images. Our grouping process consists of two steps. We carry out the first grouping process to group fragmented or duplicated 3D lines into the principal 3D lines, which can be used to construct the rooftop model, and construct the groups of lines that are parallel each other in the second step. From the grouping result, 3D rooftop models are reconstructed by the final clustering process. High-resolution IKONOS images are utilized for the experiments. The experimental result's indicate that the reconstructed building models almost reflect the actual position and shape of buildings in a precise manner, and that the proposed approach can be efficiently applied to building reconstruction problem from high-resolution satellite images of an urban area.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.505-507
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• 2003

This paper describes techniques for the automated creation of geometric 3D models of the urban area us ing two 2D laser scanners and aerial images. One of the laser scanners scans an environment horizontally and the other scans vertically. Horizontal scanner is used for position estimation and vertical scanner is used for building 3D model. Aerial image is used for registration with scan data. Those models can be used for virtual reality, tele-presence, digital cinematography, and urban planning applications. Results are shown with 3D point cloud in urban area.

• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.4
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• pp.24-29
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• 2015

Bridge construction cost estimates have generally been conducted by using historial unit-price(per meter or square meter). The traditional estimating method based on unit-price references can never completely reflect the specialty of cable supported bridge. In this paper, we have developed the system for supporting the approximate construction cost and the quantity estimation based on 3D model information in the pre-project planning phase of 3-span continuous suspension bridge with 2-pylons. First of all, we'd analyzed the design information (such as structural design report, blueprint and quantity) and the real cost data from the existing suspension bridges and derived the design variables of the bridges. We developed the BIM wizard that generates a suspension bridge model parametrically based on derived design variables. The principle material quantities of suspension bridge are calculated directly from 3-dimensional bridge model built by using the BIM wizard. We have established the system that the construction cost can be estimated more specific than the traditional estimating method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.166-171
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• 2015

In this study, an automation tool was developed for rapid evaluation of machine tool spindle designs with automated three-dimensional finite element analysis (3D FEA) using solid elements. The tool performs FEA with the minimum data of point coordinates to define the section of the spindle shaft and bearing positions. Using object-oriented programming techniques, the tool was implemented in the programming environment of a CAD system to make use of its objects. Its modules were constructed with the objects to generate the geometric model and then to convert it into the FE model of 3D solid elements at the workbenches of the CAD system using the point data. Graphic user interfaces were developed to allow users to interact with the tool. This tool is helpful for identification of a near optimal design of the spindle based on, for example, stiffness with multiple design changes and then FEAs.

• Journal of Biomedical Engineering Research
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• v.41 no.5
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• pp.195-202
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• 2020

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.1
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• pp.47-56
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• 2015

In this paper, we present an implicit method for reconstructing a 3D solid model from two 2D cross section images. The proposed method is based on the Cahn-Hilliard model for the image inpainting. Image inpainting is the process of reconstructing lost parts of images based on information from neighboring areas. We treat the empty region between the two cross sections as inpainting region and use two cross sections as neighboring information. We initialize the empty region by the linear interpolation. We perform numerical experiments demonstrating that our proposed method can generate a smooth 3D solid model from two cross section data.