• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.65-74
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• 2010

We propose a system that automatically recognizes the tense or relaxed condition of scrolling-shooting game subject that plays. Existing study compares the changed values of source of stimulation to the player by suggesting the source, and thus involves limitation in automatic classification. This study applies SOM of unsupervised learning for automatic classification and recognition of player's condition change. Application of SOM for automatic recognition of tense and relaxed condition is composed of two steps. First, ECG measurement and analysis, is to extract characteristic vector through HRV analysis by measuring ECG after having the player play the game. Secondly, SOM learning and recognition, is to classify and recognize the tense and relaxed conditions of player through SOM learning of the input vectors of heart beat signals that the characteristic extracted. Experiment results are divided into three groups. The first is HRV frequency change and the second the SOM learning results of heart beat signal. The third is the analysis of match rate to identify SOM learning performance. As a result of matching the LF/HF ratio of HRV frequency analysis to the distance of winner neuron of SOM based on 1.5, a match rate of 72% performance in average was shown.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.463-464
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• 2015

The purpose of this study is examine the relation with the academic motivation variable, cognitive style and the academic achievement, and guide to strategies of Mobile game learning development. Based on cognitive theory, the academic motivation variable has more related with academic achievement. As a result, internal motivation variables has highly positive correlation on academic self efficacy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.211-213
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• 2017

효율적인 학습활동을 위해 중요한 것 중 하나는 학습자의 학습의지다. 학습자의 학습동기를 유발할 수 있는 게임을 학습과 접목하여 학습내용으로 설정하고 프로그래밍 교육을 설계해보고자 한다. 교육도구로는 학습자들에게 친숙한 도구이자 일상생활에서 떼어놓을 수 없는 스마트 폰을 활용하고자 하며 프로그램으로는 앱 제작 프로그램인 앱 인벤터를 활용하고자 한다. 본 게임제작기반 교수학습설계를 통해 다양한 경우의 컴퓨팅 사고력을 훈련함으로 분석력, 논리력, 창의력 향상을 통한 문제해결력 신장과 제4차산업혁명시대에 적응할 수 있는 창의적 인재양성을 기대한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.69-70
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• 2020

본 논문에서는 현재 운영되고 있는 온라인 게임에서 실력을 겨루는 형태의 경쟁적인 온라인 게임들에서 사용되어지고 있는 게임 핵이 게임에 미치는 영향을 제시한다. 그리고 게임 핵을 검출하기 위한 객체 인식 기술로 실시간 정보 획득이 가능한 YOLOv3 알고리즘을 사용하였다. 이는 속도가 빠른 객체인식 기술이며 이미지 속 물체의 외관 뿐만 아니라 전체적인 컨텍스트까지 학습을 진행한다. 그리고 나아가 게임 핵 검출을 위한 개발 및 운영적 측면에서 어떻게 지원돼야 하는 등의 내용을 제시한다.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.72-77
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• 2022

Among the techniques of reinforcement learning, Q-Learning means learning optimal policies by learning Q functions that perform actionsin a given state and predict future efficient expectations. Q-Learning is widely used as a basic algorithm for reinforcement learning. In this paper, we studied the effectiveness of selecting and learning efficient paths by designing policies and rewards based on Q-Learning. In addition, the results of the existing algorithm and punishment compensation policy and the proposed punishment reinforcement policy were compared by applying the same number of times of learning to the 8x8 grid environment of the Frozen Lake game. Through this comparison, it was analyzed that the Q-Learning punishment reinforcement policy proposed in this paper can significantly increase the learning speed compared to the application of conventional algorithms.

• Journal of KIISE
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• v.45 no.1
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• pp.30-35
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• 2018

GuessWhat?! is a game in which two machine players, composed of questioner and answerer, ask and answer yes-no-N/A questions about the object hidden for the answerer in the image, and the questioner chooses the correct object. GuessWhat?! has received much attention in the field of deep learning and artificial intelligence as a testbed for cutting-edge research on the interplay of computer vision and dialogue systems. In this study, we discuss the objective function and characteristics of the GuessWhat?! game. In addition, we propose a simple solver for GuessWhat?! using a simple rule-based algorithm. Although a human needs four or five questions on average to solve this problem, the proposed method outperforms state-of-the-art deep learning methods using only two questions, and exceeds human performance using five questions.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.113-120
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• 2017

With the development of virtual reality technology, in recent years, user-friendly hand gesture interface has been more studied for natural interaction with a virtual 3D object. Most earlier studies on the hand-gesture interface are using relatively simple hand gestures. In this paper, we suggest an intuitive hand gesture interface for interaction with 3D object in the virtual reality applications. For hand gesture recognition, first of all, we preprocess various hand data and classify the data through the binary decision tree. The classified data is re-sampled and converted to the chain-code, and then constructed to the hand feature data with the histograms of the chain code. Finally, the input gesture is recognized by MCSVM-based machine learning from the feature data. To test our proposed hand gesture interface we implemented a 'Virtual Block' game. Our experiments showed about 99.2% recognition ratio of 16 kinds of command gestures and more intuitive and user friendly than conventional mouse interface.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.125-133
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• 2021

Due to Covid-19, the un-contact culture has affected society as a whole, and the methods of education conducted offline has been greatly affected. In the private education of preparing for university entrance, the public official examinations and certification acquisition, the method of online education has been shown to have positive effects. While private class and school class which have offered in off-line to cope with rapid changes caused various problems such as decline in quality for education. Due to the characteristic of design class, practical training is important. As interactive feedback between students and educators is more important than one-way of delivering knowledge while class is conducted in online, educators have a challenge when they prepare for class. This study handles the methods of online education for the purpose of practical education methods in university nowadays, Especially, the non-face-to-face education methods for game animation production. Based on this study, I propose an effective educational method with non-face-to-face class that allows students to be satisfied and increases their knowledge, beyond face-to-face class.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.661-668
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• 2022

Various lean design and construction methods such as target value design, pull planning, value stream mapping have successfully transformed the commercial building construction industry into achieving improved productivity, higher design and construction quality, and meeting the target values of construction projects. Considering the significant advantages of lean, the accelerated dissemination and adoption of lean methods and tools for construction is highly desirable. Currently, the lean design and construction body of knowledge is imparted primarily through publications and conferences. However, one of the most effective ways to impart this soft knowledge is through getting students and trainees involved in hands-on participatory games, which can quickly help them truly understand the concept and apply it to real-world problems. The COVID-19 Pandemic has raised an urgent need of developing virtual games that can be played simultaneously from various locations over the Internet, but these virtual games should be as effective as in-person games. This research develops an online 3D simulation game for Target Value Design that is as effective as in-person games or possibly better in terms of knowledge capture and retention and enjoyable environment and experience. The virtual game is tested on volunteers using feedback from pre-and post- simulation surveys to evaluate its efficacy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.73-76
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• 2022

본 논문에서는 메타버스 공간에서 패션 아이템 판매에 있어서 필수적이라 할 수 있는 온라인 가상 피팅 기술을 동작 인식 전용 디바이스가 아닌 일반 스마트폰 카메라를 활용하여 구현하는 기술을 제안한다. 가상 피팅 기술을 구현하기 위해서는 딥러닝 기법을 활용하여 입력 영상을 분석하고, 분석 결과를 토대로 인체의 전체 자세를 추정하며, 인체 사이즈의 근사값을 추출하는 과정들이 수행되어야 하는데, 현재의 스마트폰 컴퓨팅 환경은 이를 수행하기에 충분한 연산 성능을 가지지 못한다는 문제점을 가진다. 본 논문에서는 높은 비용이 요구되는 고부하 연산을 클라우드 서버를 통해 수행하는 서버 기반 프레임워크를 도입하여, 낮은 성능의 스마트폰으로도 고성능 연산이 가능한 서비스 구조를 확보하고 이를 통해 휴대성 높은 증강현실 기반의 가상 피팅 기술을 구현한다. 본 논문의 성과를 통해 메타버스 상거래의 활성화와 메타버스 본연의 의미에 충실한 가상 월드 구축에 기여할 것이라 기대한다.