• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.270-277
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• 2008

The development of a face robot basically targets very natural human-robot interaction (HRI), especially emotional interaction. So does a face robot introduced in this paper, named Buddy. Since Buddy was developed for a mobile service robot, it doesn't have a living-being like face such as human's or animal's, but a typically robot-like face with hard skin, which maybe suitable for mass production. Besides, its structure and mechanism should be simple and its production cost also should be low enough. This paper introduces the mechanisms and functions of mobile face robot named Buddy which can take on natural and precise facial expressions and make dynamic gestures driven by one laptop PC. Buddy also can perform lip-sync, eye-contact, face-tracking for lifelike interaction. By adopting a customized emotional reaction decision model, Buddy can create own personality, emotion and motive using various sensor data input. Based on this model, Buddy can interact probably with users and perform real-time learning using personality factors. The interaction performance of Buddy is successfully demonstrated by experiments and simulations.

• International Journal of Contents
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• v.7 no.1
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• pp.14-22
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• 2011

Temporal Sign Language Recognition (TSLR) from hand motion is an active area of gesture recognition research in facilitating efficient communication with deaf people. TSLR systems consist of two stages: a motion sensing step which extracts useful features from signers' motion and a classification process which classifies these features as a performed sign. This work focuses on two of the research problems, namely unknown time varying signal of sign languages in feature extraction stage and computing complexity and time consumption in classification stage due to a very large sign sequences database. In this paper, we propose a combination of Dynamic Time Warping (DTW) and application of the Single hidden Layer Feedforward Neural networks (SLFNs) trained by Extreme Learning Machine (ELM) to cope the limitations. DTW has several advantages over other approaches in that it can align the length of the time series data to a same prior size, while ELM is a useful technique for classifying these warped features. Our experiment demonstrates the efficiency of the proposed method with the recognition accuracy up to 98.67%. The proposed approach can be generalized to more detailed measurements so as to recognize hand gestures, body motion and facial expression.

• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.253-259
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• 2015

The spread of smartphones enabled the two-way communication through the Internet, and character emoticons added fun and comfort to communication among users. To figure out laughter-arousing factors, a survey about emoticon designs of Kakaotalk Itemstore was conducted, targeting university students in their twenties. An interaction of 'user-preferred emoticons' and 'laughter-arousing emoticons' was analyzed. 90% of 'user-preferred emoticons' were 'humorous emoticons', and 84% of respondents answered that there is a relationship between 'user-preferred emoticons' and 'laughter-arousing emoticons'. Consequently, a high interaction between the 'rank of emoticons' and 'laughter-arousing emoticons' was derived. Also, factors of laughter-arousing emoticons were analyzed by studying the ranks of emoticon from 1st to 8th of Kakaotalk Itemstore. Two-divisional figures reminding pure kids, maximization of emotional expression by omission or exaggeration of mouth, and smoothness by concave curves aroused laughter. Intuitively understandable gestures were employed in terms of action. Furthermore, two-divisional figures' acting with comparably small body, hands and foot to their head, and people-mimicking motions of animals with cuteness and familiarity enabled arousal of laughter. In facial expressions, humorous articulation of sad, busy or mad expression enabled positive communion among users.

• International Journal of Contents
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• v.15 no.4
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• pp.59-64
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• 2019

In recent years, emotion recognition has been an interesting and challenging topic. Compared to facial expressions and speech modality, gesture-based emotion recognition has not received much attention with only a few efforts using traditional hand-crafted methods. These approaches require major computational costs and do not offer many opportunities for improvement as most of the science community is conducting their research based on the deep learning technique. In this paper, we propose an end-to-end deep learning approach for classifying emotions based on bodily gestures. In particular, the informative keyframes are first extracted from raw videos as input for the 3D-CNN deep network. The 3D-CNN exploits the short-term spatiotemporal information of gesture features from selected keyframes, and the convolutional LSTM networks learn the long-term feature from the features results of 3D-CNN. The experimental results on the FABO dataset exceed most of the traditional methods results and achieve state-of-the-art results for the deep learning-based technique for gesture-based emotion recognition.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.3
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• pp.596-599
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• 2005

Human health is affected by not only physical conditions but also mental and social well-being. Changes of human emotions show up as gestures, facial expressions and sweating. Human emotions are affected by such automatic nerve system functions as blood pressure, blood circulation speed, heart beats, pupillary reflex, fluid transfusion, muscular contraction and digestive organs, all of which influence the holistic diseases. The Oriental Medicine sees from a perspective of unity of divinity and men that human life activities are united in terms of their physical and mental functions. From such a perspective, human Five Organs are linked with Five Mental(五神) and Seven Emotions(七情), while they are affected by each other, influencing the life activities both directly and indirectly. Based on Confucianism, Sa-Sang Theory argues that human emotions can be categorized into four energy states and therefore, that human diseases and physiological conditions there of may be determined differently depending on the Four Energies(四氣). There seems to be some common points between Sa-Sang Theory and the conventional Oriental Medicine in that human emotions affect individuals' health conditions, so there seems to be much room for mutual complementation.

• The Journal of Korean Academic Society of Nursing Education
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• v.25 no.4
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• pp.459-470
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• 2019

Purpose: The purpose of this qualitative study was to identify the nature of precocious puberty and to explore what it means in primary schools. Methods: The participants of this phenomenological study were nine primary school girls who were diagnosed with precocious puberty and experienced hormone therapeutics, applying a convenience sampling method. Data were collected from July 2017 to January 2018 through individual in-depth interviews of the participants, including gestures, facial expressions and nonverbal means. The data analysis followed the method of Giorgi. Results: The study identified 37 concepts, 12 clusters, and five themes from experiences of precocious puberty. The essential five themes were as follows: 'ashamed and concealing experience', 'there is no therapeutics option', 'difficulties in the process of therapeutics', 'difficulties in daily life', and 'ambivalence toward therapeutics'. Conclusion: The findings of this study indicate physical, psychological and social difficulties faced by girls with precocious puberty. Based on this results of the study, it is necessary to develop nursing intervention programs focusing on healthy growth and development for children with precocious puberty.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.1-12
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• 2017

This study is the academic work to explore the potential meanings of print advertisements. Linguistic features such as repetition, variation, contrast and phonological structure in the verbal texts of ads can give rise to shades-of-meaning or slight variations in advertising. The language of advertising is not only language in words. It is also a language in images, colors, and pictures. Pictures and words combine to form the advertisement's visual text.. While the words are very important in delivering the sales message, the visual text cannot be ignored in advertisements. Forming part of the visual text is the paralanguage of the ad. Paralanguage is the meaningful behaviour accompanying language, such as voice quality, gestures, facial expressions and touch in speech, and choice of typeface and letter sizes in writing. Foregrounding is the throwing into relief of the linguistic sign against the background of the norms of ordinary language. This paper focuses its discussion on the advertisements within the framework of the paradigmatic and the syntagmatic relationship. The sources of ads have been confined to Malboro. The ads were reselected based on purposive sampling methods.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.581-593
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• 2020

The purpose of this study was to examine the eye-fixation times on different parts of a student avatar and the virtual presence with two scenarios in the virtual reality-based teaching simulation. This study was to identify user attention while he or she is interacting with a student avatar. By examining where a user is gazing during a conversation with the avatar, we have a better understanding of non-verbal communication. For this study, forty-five college students (21 females and 24 males) participated in the experiment. They had a conversation with a student avatar in a virtual reality-based teaching simulation. The participants had verbal interactions with the student avatar with two scenarios. While they were having a conversation with the virtual character in the teaching simulation, their eye-movements were collected through a head-mounted display with an eye-tracking function embedded. The results revealed that there were significant differences in eye-fixation times. Participants gazed a longer time on facial expression than any other area. The fixation time on the facial expression was more prolonged than on gestures (F=3.75, p<.05). However, the virtual presence was not significantly different in two scenario levels. This result suggested that users focus on the face more than the gesture when they emotionally interact with the virtual character.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Korean Society of Costume
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• v.51 no.4
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• pp.71-80
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• 2001

Since the beginning of the 90's, Fashion shows appear to be a type of performance form of art combining with other areas to visually entertain the viewers. This can be explained by the modern tendency to escape from society which requires formality and complicated lifestyles. Fashion shows take place in a scene Influenced by the idea of post-modernism which redefines the definition of space. A church, old factory, unoccupied ground, subway stations, or even place like a waste disposal are used as a setting. The stage set is no longer the T shape run way and the procinium arch has disappeared. The gap between audience and stage has diminished and theatrical element is added to the fashion performance by using viewers living and working environments as setting of the show. The human relation with machine based on the cutting edge technology such as the stage automation, robots and mist making sprinkler system introduces new elements with spontaneity and detailed planning in the stage performance. Music also plays an Important role in attracting viewers. The sound track covers house music to techno music. Instead of music being abstract, folks orchestral music, choirs, piano. even live concert performed by pop artist provide the liveliness of the fashion show. And the catwalk itself is a performance. Model needs to be well trained as the capable talent who can handle sensitive gestures, facial expressions, dancing and choreography. The improvisatorial interaction between audience and model lead to audience participation. Models now range from pop star, ordinary people, handicapped people, to elderly and so on. John Galliano introduced the theatrical factors for the fashion show and Alexander Mcqueen approached the fashion show as the visual art of communication. Hussein Chalayan utilized high technology skewing futurism as if in a magic show. Today the Fashion show tends to be a total performance which includes audience participation, impromptu, and that break the limitation that fashion shows previously had. This will lead the fashion industry in opening new horizon of its own.