• Journal of International Society for Simulation Surgery
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• 제2권1호
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• pp.10-12
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• 2015

Purpose It has been stated that patient satisfaction is the crucial factor for determining success in plastic surgery. The convergence of medical science and computer vision has made easier to satisfy patients who wants to have plastic surgery. In this paper, we try to apply 3D face modeling in plastic surgical area. Materials and Methods The author introduces a method for accurate 3D face modeling techniques using a statistical model-based 3D face modeling approach in a mirror system. Results We could successfully obtain highly accurate 3D face shape results. Conclusion The method suggested could be used for acquiring 3D face models from 2D face image and the result obtained from this could be effectively used for plastic surgical areas.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.75-79
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• 1999

Geo-features play a key role in object-oriented or feature-based geo-processing system. So the strategy for how-to-model and how-to-manage the geo-features builds the main architecture of the entire system and also supports the efficiency and functionality of the system. Unlike the conventional 2D geo-processing system, geo-features in 3B GIS have lots to be considered to model regarding the efficient manipulation and analysis and visualization. When the system is running on the Web, it should also be considered that how to leverage the level of detail and the level of automation of modeling in addition to the support for client side data interoperability. We built a set of 3D geo-features, and each geo-feature contains a set of aspatial data and 3D geo-primitives. The 3D geo-primitives contain the fundamental modeling data such as the height of building and the burial depth of gas pipeline. We separated the additional modeling data on the geometry and appearance of the model from the fundamental modeling data to make the table in database more concise and to allow the users more freedom to represent the geo-object. To get the users to build and exchange their own data, we devised a file format called VGFF 2.0 which stands for Virtual GIS File Format. It is to describe the three dimensional geo-information in XML(eXtensible Markup Language). The DTD(Document Type Definition) of VGFF 2.0 is parsed using the DOM(Document Object Model). We also developed the authoring tools for. users can make their own 3D geo-features and model and save the data to VGFF 2.0 format. We are now expecting the VGFF 2.0 evolve to the 3D version of SVG(Scalable Vector Graphics) especially for 3D GIS on the Web.

• 디지털산업정보학회논문지
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• 제12권4호
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• pp.107-114
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• 2016

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

• 제어로봇시스템학회논문지
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• 제16권10호
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3284-3306
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• 2018

This study proposes a method to develop an authoring system(GeoMaTree) for diverse trees that constitute a virtual landscape. The GeoMaTree system enables the simple, intuitive production of an efficient structure, and supports real-time processing. The core of the proposed system is a procedural modeling based on a mathematical model and an application that supports digital content creation on diverse platforms. The procedural modeling allows users to control the complex pattern of branch propagation through an intuitive process. The application is a multi-resolution 3D model that supports appropriate optimization for a tree structure. The application and a compatible function, with commercial tools for supporting the creation of realistic synthetic images and virtual landscapes, are implemented, and the proposed system is applied to a variety of 3D image content.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2007년도 정기총회 및 학술발표대회
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• pp.418-421
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• 2007

Application이나 3D 모델로 구현된 맵 관련 위성영상, UAV 영상을 통해 현장감 있는 정보를 정확하게 얻는 것은 중요하다. 방재관련 업계에서는 3D 모델링에 근거한 재해지역 주변의 정확한 3차원 지형공간정보 취득의 필요성을 인식하고 있다. 본 논문에서는 GIS 기술을 활용하여 3D 모형을 생성하고, 각종 영상들을 로딩하고 처리하는 부분에 있어서의 방법을 제시하였다. 그리고 대상지역의 수치고도모형과 지형지물을 위해 수치 지형도를 사용하였다. 결과는 3D 모델링 기반의 간단한 application의 구현이다. 제시한 방법은 방재 관련업계의 종사자들에게 더 나은 방법을 제시하기에 활용 가능하다.

• 한국결정성장학회지
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• 제22권1호
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• pp.42-50
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• 2012

Mural Art는 빛의 색채 반응과 몰입, 확산 작용을 통하여 다양한 이미지를 나타내게 할 수 있는 디자인 작업이다. 본 논문은 천연 보석의 광학 현상을 Mural Art에 적합한 Digital Pattern으로 형성하고, 보석 및 광물의 광채와 작품 디자인과의 연관성에 대하여 고찰하였다. 작품 디자인의 상호(관련) 작용에 나타난 새로운 가능성을 광채가 아름다운 울트라 마린(Ultramarine)과 스펙트럼(Spectrum)의 색채 예술로서 벽면에 기초하여, 고해상도 Image의 그래픽 디자인으로 표현하고, 지속가능한(3D) Simulation의 Interior(Presentation) Modeling으로 활용하여 보았다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.578-581
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• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

• Composite Materials and Engineering
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• 제3권3호
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• pp.221-239
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• 2021

This paper presents a multiscale modeling method for sheet molding compound (SMC) composites through a novel bundle packing reconstruction algorithm based on a micro-CT (Computed Tomography) image processing. Due to the complex flow pattern during the compression molding process, the SMC composites show a spatially varying orientation and overlapping of fiber bundles. Therefore, significant inhomogeneity and anisotropy are commonly observed and pose a tremendous challenge to predicting SMC composites' properties. For high-fidelity modeling of the SMC composites, the statistical distributions for the fiber orientation and local volume fraction are characterized from micro-CT images of real SMC composites. After that, a novel bundle packing reconstruction algorithm for a high-fidelity SMC model is proposed by considering the statistical distributions. A method for evaluating specimen level's strength and stiffness is also proposed from a set of high-fidelity SMC models. Finally, the proposed multiscale modeling methodology is experimentally validated through a tensile test.