• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.1
• /
• pp.29-40
• /
• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.6
• /
• pp.513-519
• /
• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Journal of Korea Multimedia Society
• /
• v.17 no.12
• /
• pp.1383-1392
• /
• 2014

In this paper, we proposed a method to automatically determine the optimal radius through multi-scale LBP operation generalizing the size of radius variation and boosting learning in facial emotion recognition. When we looked at the distribution of features vectors, the most common was $LBP_{8.1}$ of 31% and sum of $LBP_{8.1}$ and $LBP_{8.2}$ was 57.5%, $LBP_{8.3}$, $LBP_{8.4}$, and $LBP_{8.5}$ were respectively 18.5%, 12.0%, and 12.0%. It was found that the patterns of relatively greater radius express characteristics of face well. In case of normal and anger, $LBP_{8.1}$ and $LBP_{8.2}$ were mainly distributed. The distribution of $LBP_{8.3}$ is greater than or equal to the that of $LBP_{8.1}$ in laugh and surprise. It was found that the radius greater than 1 or 2 was useful for a specific emotion recognition. The facial expression recognition rate of proposed multi-scale LBP method was 97.5%. This showed the superiority of proposed method and it was confirmed through various experiments.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.354-357
• /
• 2019

최근 맞벌이 가정이 많아지면서 베이비 시터를 고용해 영아를 양육하는 경우가 많아지고 있는 추세이다. 본 논문에서는 영유아 상태분석에 따른 인공지능 베이비시터 시스템에 대하여 기술하였다. 보다 상세하게는 얼굴인식을 위한 Opencv 영상처리 기법, MS(azure)API 를 이용한 머신러닝 기반의 감정분석과 악취 센서(MQ-135 Sensor)를 이용하여 영유아의 상태를 파악한다. 파악한 영유아의 상태를 바탕으로 스스로 학습하여 요람을 제어하고 어플리케이션을 통해 원격제어를 할 수 있도록 제작한 스마트 베이비시터 시스템에 관한 것이다. 이에 따라 양육에 대한 부담감이 줄어들 것으로 기대하고 양육에 대한 부담감을 조금이나마 경감 시켜 주어 저출산과 양육 지출 비용 절약으로 사회적 측면, 경제적 측면 모두에 기여할 것을 기대한다.

• Korean Journal of Social Welfare Studies
• /
• v.45 no.3
• /
• pp.35-69
• /
• 2014

This study was conducted to explore initial motherhood experience of non-married mothers who decided to raise their babies. We applied Rennie's hermeneutic grounded theory for this study in which 7 non-married mothers participated. 9 hermeneutic categories which are 'decision to give birth', 'feeling of hitting bottom', 'ambivalence toward a life in stomach', 'realization of motherhood', 'motherhood anxiety', 'the bridle of social tag', 'hope of motherhood', 'encounter with new self' and 'visage of weary life' were constructed based on 145 meaning units, 34 subordinate categories. The core category that integrates motherhood experiences of participants was postulated as living with two conflicting visages of motherhood which are a cure and a poison at the same time. Motherhood experience processes were emerged in five stages which are decision to give birth, psychological frustration, realization of motherhood, confusion, and hope and discouragement of motherhood. Three types of motherhood experience were analyzed in the study which are adaptative, conflictive, and resistant. Based on the result of the study, the motherhood experience of non-married mother who decided to raise their babies are the process of emergence of new identity called mother. The non-married mothers formed their motherhood identities as they internalize socioculturally granted motherhood ideology. Moreover, the gap between socially oriented motherhood and realistic role of motherhood led to confusion. Based on this study, we suggest intervention plans to the field of social welfare practice that will support initial motherhood of non-married mothers who decided to keep their babies.

• Journal of Broadcast Engineering
• /
• v.27 no.4
• /
• pp.499-510
• /
• 2022

This paper introduces a video editing system for senior creator who is not familiar to video editing. Based on video analysis techniques, it provide various information and delete unwanted shot. The system detects shot boundaries based on RNN(Recurrent Neural Network), and it determines the deletion of video shots. The shots can be deleted using shot-level significance, which is computed by detecting focused area. It is possible to delete unfocused shots or motion-blurred shots using the significance. The system detects object and face, and extract the information of emotion, age, and gender from face image. Users can create video contents using the information. Decorating tools are also prepared, and in the tools, the preferred design, which is determined from user history, places in the front of the design element list. With the video editing system, senior creators can make their own video contents easily and quickly.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.983-991
• /
• 2019

This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

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

• The Journal of Korean Philosophical History
• /
• no.25
• /
• pp.71-71
• /
• 2009

This study aims to provide a theoretical base for making a character education program on "how primary school students to cultivate their own right and good-minded characters." This study consists of three approaches: 1) an integrative approach based on the social and emotional learning, 2) development of integrative programs articulating three key domains directly and indirectly influencing students' character formation - school, family and local community(society), 3) maximum use of the educational institutes' moral education curriculums and the potential curriculums in the surrounding environment. In concrete, by specializing "social awareness and relationship skills" from various social and emotional ones, this study suggests an integrative program for the character education based on the theory of virtue in the Eastern philosophy. To develop such an Eastern philosophy-based integrative program for the cultivation of the social awareness and personal relationship skills, this study applies some virtue items of Eastern Ethics: for examples, 'rectification of the name(正名)' to improve skills for rational choice on the awareness and performance of social roles, 'empathy(忠恕)' to enhance the ability to share another person's feelings and emotions as if they were my own, 'reflect and seek in oneself(反求諸己)' to solve conflicts in peace and self-reflection, 'difficulty with countenance(色難)' to respond to others by understanding their situations and characters, 'select and follow good qualities of others and reform their bad qualities(擇其善者而從之, 其不善者而改之)' to make good results from various forms of personal relationship, and 'keep same respect as at first to old acquaintance(久而敬之)' to maintain good and emotional relationships. In particular, by underlining 'rectification of the name(正名)' and 'reflect and seek in oneself(反求諸己)', this study attempts to develop an alternative integrative program articulating three domains of school, family and local community.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.185-209
• /
• 2023

With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.