• Korean Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.142-149
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• 1997

This study is intended to develop a Feature based modeler. It is difficult to integrate CAD and CAM/CAPP with information that is given only by a conventional CAD system. Therefore a lot of studies have concentrated on a Feature based CAD system. But conventional Feature based modelers have had limitation on providing sufficient information related to Feature interaction. If a Feature based modeler is to be used in assembly simulation, a new Feature-based modeling method needs to be developed. Also to support collision detection between parts, we have to handle Feature interaction systematically. Therefore we suggest Cell data structure which handles interaction of Features by volume. The volume created by Feature interaction is saved as a Cell. With the Cell structure we solve problems involved with Feature interaction. This study shows how the Cell data structure can manage Feature interaction and give enough information in assembly simulation.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.108-118
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• 2013

Recently the 3D modeling techniques were developed rapidly due to rapid development of computer vision, computer graphics with the excellent performance of hardware. With the advent of a variety of 3D contents, 3D modeling technology becomes more in demand and it's quality is increased. 3D face models can be applied widely to such contents with high usability. In this paper, a 3D face modeling is attempted from a given single 2D frontal face image. To achieve the goal, we thereafter the feature points using AAM are extracted from the input frontal face image. With the extracted feature points we deform the 3D general model by 2-pass mesh warping, and also the depth extraction based on intensity values is attempted to. Throughout those processes, a universal 3D face modeling method with less expense and less restrictions to application environment was implemented and it's validity was shown through experiments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.9-16
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• 2002

This paper proposes a new 3D modeling technique using disparity-motion relationship and feature points. To generate the 3D model from real scene, generally, we need to compute depth of model vertices from the dense correspondence map over whole images. It takes much time and is also very difficult to get accurate depth. To improve such problems, in this paper, we only need to find the correspondence of some feature points to generate a 3D model of object without dense correspondence map. The proposed method consists of three parts, which are the extraction of object, the extraction of feature points, and the hierarchical 3D modeling using classified feature points. It has characteristics of low complexity and is effective to synthesize images with virtual view and to express the smoothness of Plain regions and the sharpness of edges.

• Korean Journal of Computational Design and Engineering
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• v.1 no.3
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• pp.242-256
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• 1996

Although feature-based design is a promising approach to fully integrating CAD/CAM, current feature-based design approaches seldom provide methodologies to easily define and design features. This paper proposes a new approach to integrating parametric design with feature-based design to overcome those limitations by globally decomposing a design into a set of features and locally defining and positioning each feature by geometric constraints. Each feature is defined as a parametric shape which consists of a feature section, attributes, and a set of constraints. The generalized sketching and sweeping techniques are used to simplify the process of designing features. The proposed approach is knowledge-based and its computational efficiency in geometric reasoning is improved greatly. Parametrically designed features not only have the advantage of allowing users to efficiently perform design changes, but also provide designers with a natural design environment in which they can do their work more naturally and creatively.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.581-586
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• 1996

This paper presents a feature recognition system for recognizing and extracting feature information needed for machining from design data contained in the CAD database of AutoCAD system. The developed system carries out feature recognition from an orthographic view of a press mold containing not only atomic features such as holes, pockets, and slots, but also compound features. Based on the result of feature recognition, it generates a 3-D modeling of the press mold. Especially, The feature recognition part is designed for detecting feature styles according to feature definition and classification, extracting parameters for various atomic features, and constructing necessary data structures for the recognized features.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.373-375
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• 2002

빠르게 변화하는 시장의 요구에 대응하고자 특정 도메인에 속하는 애플리케이션 간의 재사용을 높이려는 Product-Line에 대한 연구가 진행되고 있다. Product-Line에서는 도메인 내의 여러 애플리케이션 간의 차이점과 공통정을 분류하는데 Feature Modeling이라는 개념을 주로 사용하고 있다. 이러한 Feature를 추상화하여 메타 모델로 나타내고 정령과 기법을 통하여 명세화 한다면, 기존의 Feature 모델에서 발견해내지 못하는 feature들과 관련 요소들을 추출하고, 명세화를 통한 통일된 해석이 가능하며 , Feature Model에 대한 reasoning, 충돌에 대한 예측 및 면상 등의 지원이 가능할 것이다. 따라서 본 논문에서는 Multi-paradigm 명세 언어를 제공하여주는 KAOS 방법을 적용하여, 추상화 수준에서의 메타 모델을 제안하고, Feature를 명세와 하고 습득하는 방안을 제시하고자 만다.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.69-81
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• 2005

As collaborative design and configuration design gain increasing importance in product development, it becomes essential to exchange parametric CAD models among participants. Parametric CAD models can be represented and exchanged in the form of a macro file or a part file that contains the modeling history of a product. The modeling history of a parametric CAD model contains feature specifications and each feature has selection information that records the name of the referenced topological entities. Translating this selection information requires solving the problems of how to identify the referenced topological entities of a feature (persistent naming problem) and how to convert the selection information into the format of the receiving CAD system (naming mapping problem). The present paper introduces the problem of exchanging parametric CAD models and proposes a solution to naming mapping.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.149-157
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• 2001

In the video retrieval system, visual clues of still images and motion information of video are employed as feature vectors. We generate the temporal textures to express the motion information whose properties are simple expression, easy to compute. We make those temporal textures of wavelet coefficients to express motion information, M components. Then, temporal texture feature vectors are extracted using spatial texture feature vectors, i.e. spatial gray-level dependence. Also, motion amount and motion centroid are computed from temporal textures. Motion trajectories provide the most important information for expressing the motion property. In our modeling system, we can extract the main motion trajectory from the temporal textures.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.2
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• pp.105-127
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• 2003

In this paper, four different data mining techniques, two neural networks and two statistical modeling techniques, are compared in terms of prediction accuracy in the context of bankruptcy prediction. In business setting, how to accurately detect the condition of a firm has been an important event in the literature. In neural networks, Backpropagation (BP) network and the Kohonen self-organizing feature map, are selected and compared each other while in statistical modeling techniques, discriminant analysis and logistic regression are also performed to provide performance benchmarks for the neural network experiment. The findings suggest that the BP network is a better choice among the data mining tools compared. This paper also identified some distinctive characteristics of Kohonen self-organizing feature map.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.201-208
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• 1994

Many three-dimensional object modeling and display methods for computer graphics and computer vision have been developed. Recently, with the help of medical imaging devices such as computerized tomography, magnetic resonance image, etc., some of those object modeling and display methods have been widely used for capturing the shape, structure and other properties of real objects in many medical applications. In this paper, we propose the reconstruction and display method of the three-dimensional object from a series of the cross sectonal image. It is implemented by using the automatic threshold selection method and the contour following algorithm. The combination of curvature and distance, we select feature points. Those feature points are the candidates for the tiling method. As a results, it is proven that this proposed method is very effective and useful in the comprehension of the object's structure. Without the technician's responce, it can be automated.