• Journal of the HCI Society of Korea
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• v.9 no.1
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• pp.23-28
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• 2014

In this study we focus on the effect of the interaction between humans and reactive television when emotion recognition through facial expression mechanism is used. Most of today's user interfaces in electronic products are passive and are not properly fitted into users' needs. In terms of the user centered device, we propose that the emotion based reactive television is the most effective in interaction compared to other passive input products. We have developed and researched next generation cognitive TV models in user centered. In this paper we present a result of the experiment that had been taken with Fraunhofer IIS $SHORE^{TM}$ demo software version to measure emotion recognition. This new approach was based on the real time cognitive TV models and through this approach we studied the relationship between humans and cognitive TV. This study follows following steps: 1) Cognitive TV systems can be on automatic ON/OFF mode responding to motions of people 2) Cognitive TV can directly select channels as face changes (ex, Neutral Mode and Happy Mode, Sad Mode, Angry Mode) 3) Cognitive TV can detect emotion recognition from facial expression of people within the fixed time and then if Happy mode is detected the programs of TV would be shifted into funny or interesting shows and if Angry mode is detected it would be changed to moving or touching shows. In addition, we focus on improving the emotion recognition through facial expression. Furthermore, the improvement of cognition TV based on personal characteristics is needed for the different personality of users in human to computer interaction. In this manner, the study on how people feel and how cognitive TV responds accordingly, plus the effects of media as cognitive mechanism will be thoroughly discussed.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1167-1174
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• 2022

With the sustainable development and transformation of the city, public art as a business card of the famous city of culture has become a hot topic of research. The intervention of public art in public space not only brings users a sense of space experience, but also becomes a unique carrier of urban and rural image making. Although there is much research on the classification, aesthetics and function of public art, there is few quantitative research on user satisfaction. This paper takes the basic features of airport public art as a research object and the basic features of airport public art as the theoretical basis to study the impact of the basic characteristics of airport public art on user satisfaction. Research methods were based on questionnaire data of 247 people, in which models and hypotheses were tested using SPSS 21.0 software, based on the induction and extraction of nine influential factors in the basic characteristics of public art. The study found that public interpretation, media patterns, color perception, modeling form, place perception, city image and memory have significant positive effects on user satisfaction. The sharedness of public art, cognition and communication in public culture and spatial relations do not affect satisfaction. Conclusion, inspiration and prospect provide suggestions for designers and reference data and theoretical support for public art evaluation.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.55-61
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• 2020

With the development of deep learning technology and advances in computing power, video-based research is now gaining more and more attention. Video data contains a large amount of temporal and spatial information, which is the biggest difference compared with image data. It has a larger amount of data. It has attracted intense attention in computer vision. Among them, motion recognition is one of the research focuses. However, the action recognition of human in the video is extremely complex and challenging subject. Based on many research in human beings, we have found that artificial intelligence-like attention mechanisms are an efficient model for cognition. This efficient model is ideal for processing image information and complex continuous video information. We introduce this attention mechanism into video action recognition, paying attention to human actions in video and effectively improving recognition efficiency. In this paper, we propose a new 3D residual attention network using convolutional neural network based on two attention models to identify human action behavior in the video. An evaluation result of our model showed up to 90.7% accuracy.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.91-98
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• 2019

The purpose of this study was to develop and test an eye tracker focusing on early childhood participants, based on the characteristics of early childhood eye tracking studies. Eye tracking collects eye movement data of the subject, which provides scientific evidence of human cognition and thinking. The researcher built a Do It Yourself eye tracker camera module from general electronic components, and used Viewpoint analysis software from Arrington Research. The researcher compared the eye tracking data between the DIY eye tracker group and Tobii Pro eye tracker group, which provides a professional eye tracking system. Eye tracking data was collected from 52 five-year old children. The average proportion of valid trials between the two groups was compared with t test, and no significant difference was found. This result indicates that the DIY eye tracker can be used to collect valid eye tracking data from young children under certain research environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1067-1073
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• 2021

Participants in the virtual environment will have an immersive and memorable perceived experience through interacting with virtual objects. Recently, commercial virtual reality technologies have released simple and cost-effective smartphone-based head-mounted displays (HMD) and high-quality wide field-of-view (FOV) HMDs. However, due to the vergence-accommodation conflict structure of HMD and the learned cognition mechanism in real, side effects such as dizziness and nausea remain challenging to overcome. This study focuses on consistent size perception among various cognitive difference factors, which are essential for interaction with virtual objects. We verified whether the visual angle, which affects the size perception of an object in real, is also the main factor in the virtual environment. Our experiments derived the relation between the visual angle and the environmental components, shadow, and grid, which help perceive a virtual object. As a result of the regression analysis, we presented that in the small FOV HMD environment, the visual angle affects size perception, and the relation between the shadow and the grid is statistically significant.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.479-488
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• 2022

In recent years, with the rapid development of machine learning technology, research utilizing machine learning has been actively conducted in fields such as cognition, reasoning and judgment, and action among various technologies constituting intelligent systems. In order to utilize this machine learning, it is indispensable to collect data for learning. However, the types of data generated vary according to the environment in which the data is generated, and the types and forms of data required are different depending on the learning model to be used for machine learning. Due to this, there is a problem that the existing data collection method cannot be reused in a new environment, and a specialized data collection module must be developed each time. In this paper, we propose a specification-based methology for data collection in artificial intelligence system to solve the above problems, ensure the reusability of the data collection method according to the data collection environment, and automate the implementation of the data collection function.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.419-424
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• 2021

The purpose of this study is to understand the educational context including the actual learning process and learner perception using the embodied metaphor in AI education. To this end, a class was designed to utilize the embodied metaphor-based unplugged activity through a qualitative approach. Matrix analysis technique was used to analyze the data collected throughout the course of the class to analyze the experiences and perceptions according to the characteristics of the learner, and the learning context. The results of the study were: First, there was a difference according to the learner's prior experience in the effect on the representative knowledge and the subsequent practice process. Next, the embodied metaphor-based unplugged activity showed soft landing effects on practice and text coding. Finally, the organic integration of unplugged and plugged-in classes helped learners understand the potential of computational thinking.

• Therapeutic Science for Rehabilitation
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• v.10 no.2
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• pp.7-22
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• 2021

Objective : This study aimed to analyze the effect of transcranial direct current stimulation (tDCS) on cognitive function recovery in patients with stroke. Methods : Data published in Korean and foreign academic journals from 2009 to 2019 were searched using the NDSL, RISS, PubMed, and CINAHL databases. A total of 11 experimental research articles were selected based on the inclusion and exclusion criteria. A qualitative assessment was conducted, and a meta-analysis of nine results from seven of the stuides was performed using the Comprehensive Meta-Analysis 3.0 program. Results : Based on the results of the meta-analysis, the attention and memory effect sizes were 0.725 and 0.796, respectively, which were both considered a "medium effect size". Statistically significant changes were observed in both the areas (p<0.05). Conclusion : The results of this study confirmed that tDCS can be useful in the rehabilitation of patients with stroke with limited cognitive function. In addition, the application methods differed, indicating that a formalized tDCS protocol is required.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.491-496
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• 2015

Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.