• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.831-834
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• 2000

The sign-language tan be used a9 an auxiliary communication means between avatars of different languages. At that time an intelligent communication method can be also utilized to achieve real-time communication, where intelligently coded data (joint angles for arm gestures and action units for facial emotions) are transmitted instead of real pictures. In this paper we design a gesture-emotion keyframe editor to provide the means to get easily the parameter values. To calculate both joint angles of the arms and the hands and to goner-ate the in keyframes realistically, a transformation matrix of inverse kinematics and some kinds of constraints are applied. Also, to edit emotional expressions efficiently, a comic-style facial model having only eyebrows, eyes nose, and mouth is employed. Experimental results show a possibility that the editor could be used for intelligent sign-language image communications between different lan-guages.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.243-246
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• 2019

본 논문에서는 감성과 힐링, 머신러닝이라는 주제를 바탕으로 딥러닝을 통한 사용자의 얼굴표정을 인식하고 그 얼굴표정을 기반으로 음악을 재생해주는 얼굴표정 기반의 음악재생 프로그램을 제안한다. 얼굴표정 기반 음악재생 프로그램은 딥러닝 기반의 음악 프로그램으로써, 이미지 인식 분야에서 뛰어난 성능을 보여주고 있는 CNN 모델을 기반으로 얼굴의 표정을 인식할 수 있도록 데이터 학습을 진행하였고, 학습된 모델을 이용하여 웹캠으로부터 사용자의 얼굴표정을 인식하는 것을 통해 사용자의 감정을 추측해낸다. 그 후, 해당 감정에 맞게 감정을 더 증폭시켜줄 수 있도록, 감정과 매칭되는 노래를 재생해주고, 이를 통해, 사용자의 감정이 힐링 및 완화될 수 있도록 도움을 준다.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.21-28
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• 2022

People differ greatly in their capacity to persist in the face of challenges. Despite significant research, relatively little is known about cognitive factors that might be involved in perseverance. Building upon human threat-management mechanism, we predicted that perseverant people would be characterized by reduced sensitivity (i.e., longer detection latency) to threat cues. Our data from 5,898 job applicants showed that highly perseverant individuals required more time to correctly identify anger in faces, regardless of stimulus type (dynamic or static computer-morphed faces). Such individual differences were not observed in response to other facial expressions (happiness, sadness), and the effect was independent of gender, dispositional anxiety, or conscientiousness. Discussions were centered on the potential role of threat sensitivity in effortful pursuit of goals.

• Science of Emotion and Sensibility
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• v.11 no.2
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• pp.271-284
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• 2008

With an assumption that the view point of a given society and time on facial attractiveness can be inferred by analyzing popular stars' faces, the cross-cultural differences in the physical measures of Korean and foreign stars were investigated. A classification model of affective facial impressions was used to obtain the physical measures of the faces and classifying them into a face-type category. The number of face images analyzed in the study were 297 in total: 94 Korean stars, and 203 foreign stars. The results show that the common characteristics found in the cross-cultural analyses of Western and Eastern stars was a sharp face.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.613-617
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• 2021

According to the growth of the service industry, stresses from emotional labor workers have been emerging as a social problem, thereby so-called the Emotional Labor Protection Act was implemented in 2018. However, insufficient substantial protection systems for emotional workers emphasizes the necessity of a digital stress management system. Thus, in this paper, we suggest a stress detection system for customer service representatives based on deep learning facial expression recognition. This system consists of a real-time face detection module, an emotion classification FER module that deep-learned big data including Korean emotion images, and a monitoring module that only visualizes stress levels. We designed the system to aim to monitor stress and prevent mental illness in emotional workers.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.478-484
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• 2004

This study is a fundamental research for the developing 3D character contents about facial expression as a sort of non-linguistic signs, focusing on an expression of emotion factors of a person. It contributes a framework for symbolic analysis about Human's emotions along with a general review of expression. The human face is the most complex and versatile of all species. For humans, the face is a rich and versatile instrument serving many different functions. It serves as a window to display one's own motivational state. This makes one's behavior more predictable and understandable to others and improves communication. The face can be used to supplement verbal communication. A prompt facial display can reveal the speaker's attitude about the information being conveyed. Alternatively, the face can be used to complement verbal communication, such as lifting of eyebrows to lend additional emphasis to stressed word. The facial expression plays a important role under the digital visual context. This study will present a frame of facial expression categories for effective manufacture of cartoon and animation that appeal to the visual emotion of the human.

• Journal of KIISE
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• v.42 no.11
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• pp.1459-1466
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• 2015

Lockscreen is one of the most frequently encountered interfaces by smartphone users. Although users perform unlocking actions every day, there are no benefits in using lockscreens apart from security and authentication purposes. In this paper, we replace the traditional lockscreen with an application that analyzes facial expressions in order to collect facial expression data and provide real-time feedback to users. To evaluate this concept, we have implemented Quantified Lockscreen application, supporting the following contributions of this paper: 1) an unobtrusive interface for collecting facial expression data and evaluating emotional patterns, 2) an improvement in accuracy of facial expression detection through a personalized machine learning process, and 3) an enhancement of the validity of emotion data through bidirectional, multi-channel and multi-input methodology.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.137-145
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• 2005

This study is a model of research for the developing 3D character contents about facial expression as a sort of non-linguistic signs, focusing on an expression of emotion factors of a person. It contributes a framework for symbolic analysis about Human's emotions along with a general review of expression. The human face is the most complex and versatile of all species. For humans, the face is a ich and versatile instrument serving many different functions. It serves as a window to display one's own motivational state. This makes one's behavior more predictable and understandable to others and improves communication. The face can be used to supplement verbal communication. A prompt facial display can reveal the speaker's attitude about the information being conveyed. Alternatively, the face can be used to complement verbal communication, such as lifting of eyebrows to lend additional emphasis to stressed word. The facial expression plays a important role under the digital visual context. This study will present a frame of facial expression categories for effective manufacture of cartoon and animation that appeal to the visual emotion of the human.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.203-223
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• 2014

This study proposes a novel context-aware recommender system, which is designed to recommend the items according to the customer's responses to the previously recommended item. In specific, our proposed system predicts the user's emotional state from his or her responses (such as facial expressions and movements) to the previous recommended item, and then it recommends the items that are similar to the previous one when his or her emotional state is estimated as positive. If the customer's emotional state on the previously recommended item is regarded as negative, the system recommends the items that have characteristics opposite to the previous item. Our proposed system consists of two sub modules-(1) emotion prediction module, and (2) responsive recommendation module. Emotion prediction module contains the emotion prediction model that predicts a customer's arousal level-a physiological and psychological state of being awake or reactive to stimuli-using the customer's reaction data including facial expressions and body movements, which can be measured using Microsoft's Kinect Sensor. Responsive recommendation module generates a recommendation list by using the results from the first module-emotion prediction module. If a customer shows a high level of arousal on the previously recommended item, the module recommends the items that are most similar to the previous item. Otherwise, it recommends the items that are most dissimilar to the previous one. In order to validate the performance and usefulness of the proposed recommender system, we conducted empirical validation. In total, 30 undergraduate students participated in the experiment. We used 100 trailers of Korean movies that had been released from 2009 to 2012 as the items for recommendation. For the experiment, we manually constructed Korean movie trailer DB which contains the fields such as release date, genre, director, writer, and actors. In order to check if the recommendation using customers' responses outperforms the recommendation using their demographic information, we compared them. The performance of the recommendation was measured using two metrics-satisfaction and arousal levels. Experimental results showed that the recommendation using customers' responses (i.e. our proposed system) outperformed the recommendation using their demographic information with statistical significance.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.573-580
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• 2005

In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.