• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.313-316
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• 2018

In this paper, the authors reflect on how a lecturer's cross-cultural gestures affect learners from across cultures online and in the field teaching sessions for improving the service when to build an e-Learning system. The study extends to survey the way learners feel about cultural differences during a presentation from the research based on sociolinguistics research. Before starting a full-scale research, a preliminary study has been conducted to base the initial experiment, and analysis these result for main research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.9-14
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• 2015

Touch interface is widely used in a smartphone instead of a keyboard or a keypad interface that has been adopted in a PC or a featurephone, respectively. Touch interface can recognize a variety of gestures that clearly represent the distinct features of each application's input. This paper analyzes users' gesture of each application captured by the touch interface of a smartphone. Specifically, we extract touch input traces from various application categories such as game, web browser, youtube, image and e-book viewer, video player, camera, and map applications, and then analyzed them. Through this analysis, we observed a certain unique characteristics of each application's touch input, and this can be utilized in various useful areas such as identification of an application user, prevention of running an application by an illegal user, or design of a new interface convenient to a specific user.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.129-136
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• 2020

Recognizing finger movements have been used as a intuitive way of human-computer interaction. In this study, we implement an wearable device for finger motion recognition and evaluate the accuracy of several ML (Machine learning) techniques. Not only HMM (Hidden markov model) and DTW (Dynamic time warping) techniques that have been traditionally used as time series data analysis, but also NN (Neural network) technique are applied to compare and analyze the accuracy of each technique. In order to minimize the computational requirement, we also apply the pre-processing to each ML techniques. Our extensive evaluations demonstrate that the NN-based gesture recognition system achieves 99.1% recognition accuracy while the HMM and DTW achieve 96.6% and 95.9% recognition accuracy, respectively.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.27-40
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• 2021

This study aims to propose and apply a song analysis method for musical songs and acting. Prior to rehearsing a musical on stage, students and actors practice diverse exercises ranging from singing, acting and dancing. Among them, singing a musical song requires the actor not only to learn the pitch, beat and melody of the music but also to express the story and scene of the character in combination. Previous studies on analysis focused on research from the perspective of individual elements of singing, acting, and dancing rather than the proposal of comprehensive analysis methods. It is time for comprehensive analysis methods to be developed to practice musical songs and demonstrate them on stage. This study selected "Epiphany" sung by Todd from the musical Sweeney Todd(1979) as the subject of analysis. The song was analyzed in five stages: synopsis, music analysis, lyrics analysis, Uta Hagen's The Six Steps analysis, and Michael Chekhov's Psychological Gesture analysis. Through proposing and applying this step-by-step analysis method, this study verifies the usefulness of musical song analysis for practising both musical theory and practical skills at the same time and provides a base for future studies.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• Speech Sciences
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• v.13 no.2
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• pp.19-33
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• 2006

The purpose of this paper was to examine acoustical characteristics of phonatory offset-onset mechanism in the connected speech of female adults with stuttering and normal nonfluency. The phonatory offset-onset mechanism refers to the laryngeal articulatory gestures. Those gestures are required to mark word boundaries in phonetic contexts of the connected speech. This mechanism included 7 patterns based on the speech spectrogram. This study showed the acoustic features in the connected speech in the production of female adults with stuttering (n=1) and normal nonfluency (n=3). Speech tokens in V_V, V_H, and V_S contexts were selected for the analysis. Speech samples were recorded by Sound Forge, and the spectrographic analysis was conducted using Praat. Results revealed a stuttering (with a type of block) female exhibited more laryngealization gestures in the V_V context. Laryngealization gesture was more characterized by a complete glottal stop or glottal fry both in V_H and in V_S contexts. The results were discussed from theoretical and clinical perspectives.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.178-183
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• 2008

Human motion analysis is researched as a new method for human-robot interaction (HRI) because it concerns with the key techniques of HRI such as motion tracking and pose recognition. To analysis human motion, extracting features of human body from sequential images plays an important role. After finding the silhouette of human body from the sequential images obtained by CCD color camera, the skeleton model is frequently used in order to represent the human motion. In this paper, using the silhouette of human body, we propose the feature extraction method based on hybrid skeleton for detecting human motion. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.74-77
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• 2015

WiSee is by utilizing the frequency of Wi-Fi(802.11n/ac), a technique for performing the operation recognized by the user's gesture. Current motion recognition scheme are using a dedicated device (leaf motion, Kinekuto) and the recognition range is 30cm ~ 3.5m. also For recognition range increases the narrow recognition rate, there is inconvenience for maintaining a limited distance. But WiSee is used by Wi-Fi it is possible to anywhere motion recognition if available location. Permeability also has advantages as compared with the conventional recognition method. In this paper I take a look at the operation process and the recent trend of WiSee.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.171-180
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• 2013

Generally, when we apply zernike moments value for matching, we can use those moments value obtained from projecting image information under circumscribed circle to zernike basis function. However, the problem is that the power of discrimination can be reduced because hand images include lots of overlapped information due to its special characteristic. On the other hand, when distinguishing hand poses, information in specific area of image information except for overlapped information can increase the power of discrimination. In this paper, in order to solve problems like those, we design R3 ring mask by combining image obtained from R2 ring mask, which can weight information of the power of discrimination and image obtained from R1 ring mask, which eliminate the overlapped information. The moments which are obtained by R3 ring mask decrease operational time by reducing dimension through principle component analysis. In order to confirm the superiority of the suggested method, we conducted some experiments by comparing our method to other method using seven different hand poses.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.1083-1089
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• 2015

Background: Compliance with California's smoke-free restaurant and bar policies may be more a function of social contingencies and less a function of legal contingencies. The aims of this study were: 1) to report indications of compliance with smoke-free legislation in Korean bars and restaurants in California; 2) to examine the demographic, smoking status, and acculturation factors of who smoked indoors; and 3) to report social cues in opposition to smoking among a sample of Koreans in California. Materials and Methods: Data were collected by telephone surveys administered by bilingual interviewers between 2007-2009, and included California adults of Korean descent who visited a Korean bar or restaurant in a typical month (N=2,173, 55% female). Results: 1% of restaurant-going participants smoked inside while 7% observed someone else smoke inside a Korean restaurant. Some 23% of bar-going participants smoked inside and 65% observed someone else smoke inside a Korean bar. Presence of ashtrays was related to indoor smoking in bars and restaurants. Among participants who observed smoking, a higher percentage observed someone ask a smoker to stop (17.6%) or gesture to a smoker (27.0%) inside Korean restaurants (N=169) than inside Korean bars (n=141, 17.0% observed verbal cue and 22.7% observed gesture). Participants who smoked inside were significantly younger and more acculturated than participants who did not. Less acculturated participants were significantly more to likely to be told to stop smoking. Conclusions: Ten years after implementation of ordinances, smoking appears to be common in Korean bars in California.