• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1035-1045
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• 2004

In this paper, we describe a method that can recognize gestures and evaluate the degree of the gestures from sequential gesture images by using Gesture Feature Space. The previous popular methods based on HMM and neural network have difficulties in recognizing the degree of gesture even though it can classify gesture into some kinds. However, our proposed method can recognize not only posture but also the degree information of the gestures, such as speed and magnitude by calculating distance among the position vectors substituting input and model images in parametric eigenspace. This method which can be applied in various applications such as intelligent interface systems and surveillance systems is a simple and robust recognition algorithm.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.389-401
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• 2012

This paper derives a benchmark dose(BMD) and its 95% lower confidence limit(BMDL) using a semi-parametric regression model for small lead based changes in attention-deficit hyperactivity disorder(ADHD) scores in the first wave of the Children's Health and Environment Research(CHEER) survey data, which have been regularly collected in South Korea since 2005. Ha et al. (2009) showed that the appearance of ADHD symptoms had a borderline trend of increasing with the blood lead concentration. Butdz-J${\o}$rgensen (EFSA, 2010a) derived the BMDL of lead corresponding to a benchmark region of 1 full intelligent quotient (IQ) score using the raw data in Lanphear et al. (2005, EHP). European Food Safety Authority (EFSA, 2010b) determined the BMDL of $1.2{\mu}g/dl$ as a reference point for the characterization of lead when assessing the risk of the intellectual deficit measured by IQ scores. Kim et al. (2011) indicated that an even lower BMDL could be obtained based on the ADHD score; however, the BMDLs depended heavily upon the model assumptions. We show in this paper that a semi-parametric approach resolves the model dependence of BMDLs.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.115-123
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• 2003

It's difficult to find efforts for individualization other than suggesting simple, branching level learning materials among the developed courseware. The reason is primarily attributed to the facts that the courseware itself is not flexible, a fixed structure which is not reusable, and numerous costs and time should be consumed to develop one. In the same context of the appearance of the object-oriented concept in the method of software development, the concept of 'learning object' has appeared in the development of courses and contents, paving the way toward the possibility of designing versatile courses through the learning object. In the learning object-based course design, however, it still has similar shape and structure to the existing courseware, and the effort to realize the individualized learning by utilizing the learning object is not sufficient, as well. In this study, I suggest a outlined learning object model which can support the individualized learning by expanding the existing learning object, and based on th is model. design a instructional model that can show an individualized learning path, based on the ADDIE model.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.54-60
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• 2004

Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.100.4-100
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• 2002

For visual navigation, mobile robot can use a stereo camera which has large field of view. In this paper, we propose an algorithm to detect and recognize human face on the basis of such camera system. In this paper, a new coarse to fine detection algorithm is proposed. For coarse detection, nearly face-like areas are found in entire image using dual ellipse templates. And, detailed alignment of facial outline and features is performed on the basis of view- based multiple appearance model. Because it hard to finely align with facial features in this case, we try to find most resembled face image area is selected from multiple face appearances using most distinguished facial features- two eye...

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.714-718
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• 2009

3D reconstruction of a human face from an image sequence remains an important problem in computer vision. We propose a method, based on a factorization algorithm, that reconstructs a 3D face model from short image sequences exhibiting rotational motion. Factorization algorithms can recover structure and motion simultaneously from one image sequence, but they usually require that all feature points be well tracked. Under rotational motion, however, feature tracking often fails due to occlusion and frame out of features. Additionally, the paucity of images may make feature tracking more difficult or decrease reconstruction accuracy. The proposed 3D reconstruction approach can handle short image sequences exhibiting rotational motion wherein feature points are likely to be missing. We implement the proposal as a reconstruction method; it employs image sequence division and a feature tracking method that uses Active Appearance Models to avoid the failure of feature tracking. Experiments conducted on an image sequence of a human face demonstrate the effectiveness of the proposed method.

• Journal of the Korea Safety Management & Science
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• v.4 no.4
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• pp.97-108
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• 2002

This study deals with the application of knowledge-based engineering and a methodology for the assessment & measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach. To improve the quality of results, the membership functions must be approximated based on heuristic considerations. Conventionally, it is not always easy to obtain a system reliability for components with different individual failure probability density functions(p.d.f.), We utilize fuzzy set theory to solve the adequacy of the conventional probability in accounting and processing of built-in uncertainties in the probabilistic data. The purpose of this study is to propose the framework of knowledge-based engineering through integrating the various sources of knowledge involved in a FTA.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.606-611
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• 2009

This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred impression on users. Physical parameters of the 3D objects that might strongly contribute to their visual impressions are sought through computational investigation of the impression ratings obtained for learning samples. "Car body" was selected as the class of 3D objects to be investigated. A morphable 3D model of car bodies that describes the variations in appearance using a smaller number of parameters was obtained. Based on each car body's rating for the impression of speediness obtained by paired comparison, the visual impression was transformed by manipulating the parameters defined in the morphable 3D model. The validity of the proposed method was confirmed by psychological experiments. A new scheme is also proposed to properly re-sample a novel object of a peculiar shape so that such an object could also be represented by the morphable 3D model.

• Journal of Fashion Business
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• v.26 no.1
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• pp.53-67
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• 2022

The purpose of this study was to compare the appearance similarity between a 3D virtual wedding dress, and a model wearing real dress, and production efficiency, and the possibility of achieving similar results with 3D digital technology. Five wedding dresses for small weddings under the theme of 'Dream Series', were designed and produced in virtual and real dresses to quantitatively compare and analyze the appearance similarity and production efficiency. Experts compared the appearance similarity on the silhouettes, colors, materials, and details, and production efficiency was compared with time and cost. Based on our results, 3D virtual images of four out of the five dresses were similar to the real images. Our efficiency evaluation results showed that the manufacturing time was 45.4% shorter, and the manufacturing cost was 46.1% less than the existing method. This indicated that the wedding dress manufacturing process using 3D virtual software was time and cost saving competitive. Our results also confirmed that 3D virtual software technology has the potential to increase the efficiency of designing and production, and therefore an increase in competitiveness and sales of wedding dresses. Furthermore, 3D technology allows consumers to select and order wedding dresses online through 3D virtual software. This is a great advantage, and it highlights the significance of this research study.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.471-481
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• 2015

This paper presents the robot vision control schemes using Extended Kalman Filter (EKF) method for the slender bar placement in the appearance of obstacles during robot movement. The vision system model used for this study involves the six camera parameters($C_1{\sim}C_6$). In order to develop the robot vision control scheme, first, the six parameters are estimated. Then, based on the estimated parameters, the robot's joint angles are estimated for the slender bar placement. Especially, robot trajectory caused by obstacles is divided into three obstacle regions, which are beginning region, middle region and near target region. Finally, the effects of number of obstacles using the proposed robot's vision control schemes are investigated in each obstacle region by performing experiments of the slender bar placement.