• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.499-505
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• 2006

거울은 인간이 자신의 모습을 들여다 보기 위해 오랜 세월 동안 이용했던 친숙한 도구이다. 디지털 기술의 발달로 우리는 빛과 정보를 함께 반사해 주는 거울에 대한 여러가지 접근들을 보아 왔다. 전통적인 거울은 빛의 즉각적인 반사에 의해 일어나는 자동적인 시각적 피드백 덕분에 특별한 조작이 필요하지 않으나, 빛과 정보가 함께 반사되는 디지털 거울에서는 다른 형태의, 좀더 적극적인 사용자 인터랙션을 기대할 수 있다. 본 논문에서는 사용자와 거울간의 거리에 따른 행태 조사를 중심으로 인터랙션 유형의 사례 분류 및 사용자 조사 연구를 정리하였다. 이를 바탕으로 거리에 따라 다른 사용자 요구사항을 충족하는 디지털 거울에 적합한 조작 인터페이스를 제안하고, 초기 모델로 회전식 적외선 격자를 이용한 조작, 비젼 기반의 정면 이미지 획득 및 얼굴 확인, 그리고 적외선 위치확인을 통해 사용자와 인터랙션하는 거울을 설계하였다. 본 연구에서는 거울과의 인터랙션에서 나타나는 사용자의 요구사항을 토대로 여러 비접촉식 거울 인터페이스를 설계하고 시스템에 적용한 사례를 분석한다. 아울러 결과물의 초기모델에 대한 분석을 통해 더 개선된 형태의 '거울을 응용한 시스템'의 설계 가능성을 보일 수 있다.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.19-27
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• 2011

The humanoid creatures like Na'Vi in 'Avatar' remind the audience of a few actors' faces in the movie, enhance realism in film through combining CG and Live action which are related to the story. The design of face-recognizable humanoid creature is expected to be used in many ways; not only in film, but also in newest media. This research proposes to apply the main concept of Caricature which is 'exaggeration' of distinctive face elements from their prototypes for 'likeness' with the subjects. Also, it provides the idea of extracting the distinctive features of a face and combining the exaggerated subject as those features with an imaginary creature-other species, alien, etc. Finally, it proves the effectiveness of the design process with some experiments.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.113-115
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• 2005

This thesis presents a method for 3D modeling of facial expression from frontal and mirror-reflected multi-image. Since the proposed system uses only one camera, two mirrors, and simple mirror's property, it is robust, accurate and inexpensive. In addition, we can avoid the problem of synchronization between data among different cameras. Mirrors located near one's cheeks can reflect the side views of markers on one's face. To optimize our system, we must select feature points of face intimately associated with human's emotions. Therefore we refer to the FDP (Facial Definition Parameters) and FAP (Facial Animation Parameters) defined by MPEG-4 SNHC (Synlhetic/Natural Hybrid Coding). We put colorful dot markers on selected feature points of face to detect movement of facial deformation when subject makes variety expressions. Before computing the 3D coordinates of extracted facial feature points, we properly grouped these points according to relative part. This makes our matching process automatically. We experiment on about twenty koreans the subject of our experiment in their late twenties and early thirties. Finally, we verify the performance of the proposed method tv simulating an animation of 3D facial expression.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.243-248
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• 2014

In this paper, we propose a method to recognize the facial expressions by selecting face elements and finding its status. The face elements are selected by using image area segmentation method and the facial expression is decided by using the normal distribution of the change rate of the face elements. In order to recognize the proper facial expression, we have built database of facial expressions of 90 people and propose a method to decide one of the four expressions (happy, anger, stress, and sad). The proposed method has been simulated and verified by face element detection rate and facial expressions recognition rate.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.269-277
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• 2006

In this paper, we propose an interactive system that generates emotional expressions from arm gestures. By extracting relevant features from key frames, we can infer emotions from arm gestures. The necessary factor for real-time animation is tremendous frame rates. Thus, we propose processing facial emotion expression with 3D application for minimizing animation time. And we propose a method for matching frames and actions. By matching image sequences of exagerrated arm gestures from participants, they feel that they are communicating directly with the portraits.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.3 s.43
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• pp.243-250
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• 1992

The purposes of this research were to analyze factor structure and the face image to hairstyles which was made by Computer graphic simulation. To select ten hairstyle, a standard face selected between women of $20\~25$ years, and four factor (straight, curl, hair length, front hair, part hair) which were made of stand of hairstyle were applied. The results were as follows; 1 face image factor by hairstyle variation were found to five factor; negative and pogitive, indivisuality, youthfulness, unbanity, intelligence. 2. The result of analysis to face image by hairstyle factor were (1) In the hair state, straight hair was explained by the youthful, pure, decent image than curl. (2) In the hair length, the longer hair was explained by the more feminine, softness image. The shorter hair was explained by the more vigorous, youthful image. (3) In the presence of front hair, bang hair was explained by the commonness, moderate, classical image than all back hair (4) In the part hair, part hair was explained by the modern and unbanity image than no part hair.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.379-380
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• 2018

Previoisly presented "Implementation to pupil motion recognition system using convolution neural network".is improved. Using OpenCV, face and eye areas are detected, and then configure the neural network using Numpy. This pupil motion recognition system is based on the Numpy for configuring and calculating the neural network. This system is implemented on DE1-SOC.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.497-502
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• 2016

Shape Contexts Recognition(SCR) is a technology recognizing shapes such as figures and objects, greatly supporting technologies such as character recognition, motion recognition, facial recognition, and situational recognition. However, generally SCR makes histograms for all contours and maps the extracted contours one to one to compare Shape A and B, which leads to slow progress speed. Thus, this paper has made simple yet more effective algorithm with optimized contour, finding the outlines according to shape figures and using the improved Douglas-Peucker algorithm and Harris corner detector. With this improved method, progress speed is recognized as faster.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.3_4
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• pp.515-526
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• 2002

The purpose of this study will find out the primary element of point make-up image perception, the point make-up image perception by point make-up trend and demographic variables such as sex and age. And this study will show the preferences of the point make-up. This study is based on the quasi-experimental study method with contents analysis method and experimental method. And content ana]isis is primarily based on the color trend and cosmetics colors which were suggested by a fashion magazine. Experiment was conducted by gathering opinions by poll, with the model wearing different make-ups and checking the typical reactions of people. To summarize, sex and age were found out to be influential variable to distinguish color perception abilities. This could verify that point make-up was important factor, influencing on the face image perception. also, face make-up effect could be maximized with Natural or common color groups rather than trend-oriented color group selections. And the polled preferred Natural color group with no point make-up or Classic color group to any other color group.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.