• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.6
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• pp.1023-1038
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• 2022

In societies emphasizing the importance of youthful appearance, attitudes toward aging are closely related to how individuals perceive their own bodies, which can be a major determinant of psychological well-being among older adults. The purpose of this study was to examine the associations between attitudes toward aging, positive body image, and life satisfaction among older Korean adults, based on relative deprivation theory and social identity theory. Employing an online survey questionnaire, data was collected from 408 Korean aged 65 and over. The proposed research model was examined via partial least square structural equation modeling (PLS-SEM). Results revealed that higher levels of psychosocial loss were associated with lower positive body image, while higher levels of physical change and psychological growth - a good example were associated with higher positive body image. Higher levels of positive body image were associated with higher life satisfaction. Overall, positive attitudes toward aging may increase positive body image and life satisfaction among older adults, controlling for subjective financial and health status. The results of this study emphasize that we should not overlook the importance of positive body image in psychological well-being among older adults.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.35-37
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• 2007

Super resolution using stochastic approach which based on the Bayesian approach is to easy modeling for a priori knowledge. Generally, the Bayesian estimation is used when the posterior probability density function of the original image can be established. In this paper, we introduced the improved MAP algorithm based on Bayesian which is stochastic approach in spatial domain. And we presented the observation model between the HR images and LR images applied with MAP reconstruction method which is one of the major in the SR grid construction. Its test results, which are operation speed, chip size and output high resolution image Quality. are significantly improved.

• Journal of the Korea Computer Graphics Society
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• v.6 no.4
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• pp.15-22
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• 2000

One of the main research trends in image based modeling and rendering is how to implement plenoptic function. For this purpose, this paper proposes a novel approach based on a set of randomly placed panoramas. The proposed approach, first of all, adopts a simple computer vision technique to approximate omni-directional depth information of the surrounding scene, and then corrects/interpolates panorama images to generate an output image at a vantage viewpoint. Implementation results show that the proposed approach achieves smooth navigation at an interactive rate.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.41-47
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• 2006

The range-based method is easy to get the 3D data in detail, but the image-based is not. In this paper. employing the magnifying lens. the new approach to get the 3D data in detail is suggested. The magnifying lens amplifies the disparity in stereo vision system and the amplification of disparity is to increase the resolution of the depth. We mathematically and experimentally verifies the fact to amplify the disparity and suggests the method to improve the original 3D data with the detail 3D data.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.59-69
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• 2007

In the video with a various environment, background modeling is important for extraction and recognition the moving object. For this object recognition, many methods of the background modeling are proposed in a process of preprocess. Among these there is a Kumar method which represents the Queue-based background modeling. Because this has a fixed period of updating examination of the frame, there is a limit for various system. This paper use a background modeling based on the queue. We propose the method that major parameters are decided as adaptive by background model. They are the queue size of the sliding window, the sire of grouping by the brightness of the visual and the period of updating examination of the frame. In order to determine the factors, in every process, RCO (Ratio of Correct Object), REO (Ratio of Error Object) and UR (Update Ratio) are considered to be the standard of evaluation. The proposed method can improve the existing techniques of the background modeling which is unfit for the real-time processing and recognize the object more efficient.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.12
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• pp.1853-1861
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• 2009

Body sizing of has been recognized as an important element affecting the degree of customer satisfaction in the apparel industry. Recent developments in IT technologies have enabled more studies in custom-made apparel systems that comply with the diverse demands from customers in many countries. Diverse methods to obtain personal physical size are being studied. This study estimates the accuracy by developing the system in which the data of length and girth can be calculated through changing a modeling by comparing the data with circular 3-dimensional physical configuration data. This information was computed from the process (such as the conversion to a standardize image) which utilizes the image capture of 2-dimensional three sides (front, side, and rear), contour tracing, and key-node selection and by realizing it in the real world.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.166-172
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• 2014

Image classification is an important problem in computer vision. However, it is a very challenging problem due to the variability, ambiguity and scale change that exists in images. In this paper, we propose a method of a hypergraph based modeling can consider the higher-order relationships of semantic attributes of a scene image and apply it to a scene image classification. In order to generate the hypergraph optimized for specific scene category, we propose a novel search method based on a probabilistic subspace method and also propose a method to aggregate the expression values of the member semantic attributes that belongs to the searched subsets based on a linear transformation method via likelihood based estimation. To verify the superiority of the proposed method, we showed that the discrimination power of the feature vector generated by the proposed method is better than existing methods through experiments. And also, in a scene classification experiment, the proposed method shows a competitive classification performance compared with the conventional methods.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1885-1888
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• 2004

In order to render 3D model of the bone, the stack of cross-sectional images must be reconstructed from a series of X-ray radiographs, served as the projections. In the case where the distance between x-ray source and detector is not infinite, image reconstruction from projection based on parallel-beam geometry provides an error in the cross-sectional image. In such case, image reconstruction from projection based on conebeam geometry must be exercised instead. This paper is devoted to the determination of detector center for SART conebeam Technique which is critically effect the performance of the resulting 3D modeling.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.206-211
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• 2011

In this paper, a fire detection algorithm based on video processing is proposed. At the first stage, background image extracted from CCTV video input signal, and then foreground image were separated by differencing CCTV input signal from background image. At the second stage, candidated area were extracted by using color information from foreground image. At the final stage, smoke or flame characteristic area were separated by using Gaussian mixture modeling applied to candidated area, and then fire can be detected. Through real experiments at the inner room, it is shown that the proposed system works well.