• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.61-71
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• 2019

Due to the limit of the time length of advertisement, facial expressions among the types of nonverbal communication are much more expressive and convincing to appeal to costumers. The purpose of this paper is not only to investigate how facial expressions are portrayed but also to examine how facial expressions convey emotion in TV advertisements. Research subjects are TV advertisements of and which had the wide range of popularity for customer known as one of the most touching commercials. The research method is Facial Action Coding System based on the theoretical perspective of a discrete emotions and designed to measure specific facial muscle movements. This research is to analyse the implications of facial expressions in the both TV ads by using FACS based on Psychology as well as anatomy. From the all the result of this, it is shown that the facial expressions portrayed with the conflict of emotional states and the dramatic emotional relief of the heroin could move more customers' emotions.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.80-88
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• 2019

With more emphasis on emotional communication with users in product design field, designers' clear and prompt grasp of user's emotion has become the core activity in product design research. To increase the flexibility applying emotion measurement in the process of product design, this study has used Facial Action Coding System (FACS) of behavioral emotion measurement method in product design evaluation. To select specimens, it has flexibly used the emotional product Image Map. Then this study has selected six product irritants inducing positive, negative and neutral emotions, and conducted FACS experiment with ordinary product users of 20 generations as the experimental subject, and analyzed users' emotional state in response to the irritants through their facial expressions. It also analyzes the advantages and disadvantages of FACS in the process of product design, such as "recording users' unconscious facial expressions" and puts forward some applicable schemes, such as "choosing a product stimulus with high user response". It is expected that this paper can be helpful to the flexibility of FACS as a method to predict user's emotion in advance at the trial stage of product design before launching them to the market.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.512-517
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• 2011

In this paper, we propose an Active Shape Model (ASM) and Lucas-Kanade (LK) optical flow-based feature extraction and analysis method for analyzing the emotional features from facial images. Considering the facial emotion feature regions are described by Facial Action Coding System, we construct the feature-related shape models based on the combination of landmarks and extract the LK optical flow vectors at each landmarks based on the centre pixels of motion vector window. The facial emotion features are modelled by the combination of the optical flow vectors and the emotional states of facial image can be estimated by the probabilistic estimation technique, such as Bayesian classifier. Also, we extract the optimal emotional features that are considered the high correlation between feature points and emotional states by using common spatial pattern (CSP) analysis in order to improvise the operational efficiency and accuracy of emotional feature extraction process.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1015-1016
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• 2008

In this paper, the method which searchs a character of face and transforms it by FACS(Facial Action Coding System) for face modeling is suggested. FACS has a function to build an expression of face to AUs(Action Units) and make various face expressions. The system performs to find accurate Action Units of sample face and use setted AUs. Consequently it carries out the coefficient for transforming face model by 2D AUs matching.

• Korean Journal of Child Studies
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• v.24 no.6
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• pp.15-31
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• 2003

This study examined the effects of emotion inducing contexts on types of infants smiling. Facial expressions of forty-five 11-to 15-month-old infants were videotaped in an experimental lab with positive and negative emotional contests. Infants' smiling was identified as the Duchenne smile or non-Duchenne smile based on FACS(Facial Action Coding System, Ekman & Friesen, 1978). Duration of smiling types was analyzed. Overall, infants showed more smiling in the positive than in the negative emotional context. Occurrence of Duchenne smiling was more likely in the positive than in the negative context and in the peek-a-boo than in the melody toy condition within the same positive context. Non-Duchenne smiling did not differ by context.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1121-1122
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• 2008

By using FACS(Facial Action Coding System) and linear interpolation, a 3D facial robot simulator is developed in this paper. This simulator is based on real facial robot and synchronizes with it by unifying protocol. Using AUs(Action Unit) of each 5 basic expressions and linear interpolation makes more various dynamic facial expressions.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.732-734
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• 2023

Facial Action Units Detection (FAUs) problem focuses on identifying various detail units expressing on the human face, as defined by the Facial Action Coding System, which constitutes a fine-grained classification problem. This is a challenging task in computer vision. In this study, we propose a Prompt Tuning approach to address this problem, involving a 2-step training process. Our method demonstrates its effectiveness on the Affective in the Wild dataset, surpassing other existing methods in terms of both accuracy and efficiency.

• Design Convergence Study
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• v.16 no.6
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• pp.137-152
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• 2017

This research aims to develop the companion robot experience design for elderly in korea based on needs-function deploy matrix of robot and emotion expression research of robot in multimodal interaction. First, Elder users' main needs were categorized into 4 groups based on ethnographic research. Second, the functional elements and physical actuators of robot were mapped to user needs in function- needs deploy matrix. The final UX design prototype was implemented with a robot type that has a verbal non-touch multi modal interface with emotional facial expression based on Ekman's Facial Action Coding System (FACS). The proposed robot prototype was validated through a user test session to analyze the influence of the robot interaction on the cognition and emotion of users by Story Recall Test and face emotion analysis software; Emotion API when the robot changes facial expression corresponds to the emotion of the delivered information by the robot and when the robot initiated interaction cycle voluntarily. The group with emotional robot showed a relatively high recall rate in the delayed recall test and In the facial expression analysis, the facial expression and the interaction initiation of the robot affected on emotion and preference of the elderly participants.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.476-483
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• 2014

The purpose of this study was to make a suitable images for korean emotional expressions. KSFI(Korean Standard Facial Image)-AUs was produced from korean standard apperance and FACS(Facial Action coding system)-AUs. For the objectivity of KSFI, the survey was examined about emotion recognition rate and contribution of emotion recognition in facial elements from six-basic emotional expression images(sadness, happiness, disgust, fear, anger and surprise). As a result of the experiment, the images of happiness, surprise, sadness and anger which had shown higher accuracy. Also, emotional recognition rate was mainly decided by the facial element of eyes and a mouth. Through the result of this study, KSFI contents which could be combined AU images was proposed. In this future, KSFI would be helpful contents to improve emotion recognition rate.