• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.591-600
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• 2015

Recently high interest in health and fitness has led to vibrant researches for the active fitness system to learn and enjoy the exercise program for oneself. In this paper, we design and implement the active spinning training system which enables user to have self-learning and experience of customized spinning training program by the biometric and movement information acquired from user's physiological signals. The proposed system provides the appropriate difficulty of spinning program which reflects the concordance rate of spinning dance gestures and the amount of exercising by analyzing the physical status of participant from his brain and pulse waves and recognizing the skeletal movement in real time. For the higher exercise effect, the system offers a virtual personal trainer to show the correct poses and controls the level of difficulty depending on the concordance rate of participant's motions. The experiment with various participants through the proposed system shows that it is able to help users in getting the available exercise effect in comparatively short time.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.406-425
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• 2019

The purpose of this study is to analyze The Effect of Teacher Participation-oriented Education Program (TPEP) centered on Multi-Faceted Analysis of Elementary Science Classes on the Class Expertise of novice teacher. First, in order to develop the TPEP, lectures and exploratory science classes were analyzed using imaging and eye-tracking techniques. In this study, the TPEP was developed in five stages: image analysis, eye analysis, teaching language analysis, gesture analysis, and class development. Participants directly analyzed the classes of experienced and novice teachers at each stage. The TPEP developed in this study is different from the existing teacher education program in that it reflected the human performance technology aspects. The participants analyzed actual elementary science classes in a multi-faceted way and developed better classes based on them. The results of this study are as follows. First, at the teacher training institutions and the school sites, pre-service teachers and novice teachers should be provided with various experiences in class analysis and multi-faceted analysis of their own classes. Second, through this study, we were able to identify the limitations of existing class observations and video analysis. Third, the TPEP should be developed to improve the novice teachers' class expertise. Finally, we hope that the results of this study are used as basic data in developing programs to improve teachers' class expertise in teacher training institutions and education policy institutions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.861-864
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• 2007

본 논문에서는 카메라-투영 시스템에서 비전에 기반을 둔 팔동작 인식을 위한 새로운 알고리즘을 제안하고 있다. 제안된 인식방법은 정적인 팔동작 분류를 위하여 푸리에 변환을 사용하였다. 팔 분할은 개선된 배경 제거 방법을 사용하였다. 대부분의 인식방법들이 같은 피검자에 의해 학습과 실험이 이루어지고 상호작용 이전에 학습단계가 필요하다. 그러나 학습되지 않은 다양한 상황에 대해서도 상호작용을 위해 동작 인식이 요구된다. 그러므로 본 논문에서는 인식 작업 중에 검출된 불완전한 동작들을 정정하여 적용하였다. 그 결과 사용자와 독립되게 동작을 인식함으로써 새로운 사용자에게 신속하게 온라인 적용이 가능하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1967-1983
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• 2020

The goal of this paper is to analyze and build an algorithm to recognize hand gestures applying to smart home applications. The proposed algorithm uses image processing techniques combing with artificial neural network (ANN) approaches to help users interact with computers by common gestures. We use five types of gestures, namely those for Stop, Forward, Backward, Turn Left, and Turn Right. Users will control devices through a camera connected to computers. The algorithm will analyze gestures and take actions to perform appropriate action according to users requests via their gestures. The results show that the average accuracy of proposal algorithm is 92.6 percent for images and more than 91 percent for video, which both satisfy performance requirements for real-world application, specifically for smart home services. The processing time is approximately 0.098 second with 10 frames/sec datasets. However, accuracy rate still depends on the number of training images (video) and their resolution.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.818-830
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• 2016

The purpose of this study is to examine the effects of the parents listening guidance program, which allows the parents to understand their hearing impaired children and how to listen at home, on the communication skills of the hearing impaired children. The research subjects were 3 hearing impaired children who did not accompany with the intellectual, emotional and behabioral problems, and the listening guidance has been performed for their parents for 3 months through the listening guidance program. The changes in the communication skills in the hearing impaired children were observed comparing before and after the education. In the results, first, the receptive language skill of the hearing impaired children was improved after than before the parents listening guidance. Second, the expressive language skill of the hearing impaired children was improved after than before the parents listening guidance, too. Third, in the communication behavior of the hearing impaired children, the phonation and the speech production were increased together with the gesture after the parents listening guidance. In conclusion, it is deemed that the parents listening guidance program would have positive influence on the communication behavior of the hearing impaired children.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.151-161
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• 2009

In this paper, we propose a serious game which aims to draw the interest of rehabilitants and increase their locomotive ability with an infrared ray(IR) pen interface. The proposed game focuses on providing easy-to-manipulate cognitive rehabilitation environments. In order to achieve the goal, we devised new game interface composed of a Wiimote controller and a IR pen. Moreover, SVM(support vector machine) algorithm was employed for gesture recognition. The proposed game can be successfully utilized not only for rehabilitants but also for aged persons in preventing dementia and promoting their health.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.408-416
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• 2017

This researcher looked at the characteristics of "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" acting techniques focused on body expressions and sought to utilize it as training method for modern actors. 'Body postponement as a symbol' is a key characteristic of "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" acting techniques, and each facial expression, gesture, and movement performed by an actor has a specific meaning. Therefore, the study on "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" has been treated as a major study mainly in the non-realistic expression style or the body-centered acting theory. Therefore, a study on "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" acting techniques was mainly dealt with as a major research subject in the nonrealistic expression style or body-centered acting theory. This study, on the other hand, emphasized the importance of research on the utilization plan of actor training, which can be usually used in realistic plays as well as non-realistic plays. According to psychologists such as Damasio and Eckman, internal impulses can also be triggered through expressions and actions associated with emotions. In addition, not only acting through the actor's inner impulse, but also expression of the actor's faithful external emotion can trigger the emotion of the audience. Such a case can be a psychological basis that "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" acting techniques, which defines rasa and expresses it physically, can be used as a methodology to enhance inner truth. Therefore, the study on the actor training utilizing ing "$N\bar{a}tya$ $\acute{s}\bar{a}stra$" can be applied as an effective approach in the study of contemporary acting theory which intends to integrate inner impulse and external expression.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2
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• pp.90-94
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• 2000

In this paper, we propose an efficient method of estimating a critical threshold which is used to reject unreliable patterns in a HMM based recognition system. The rejection methods based on the anti-models which are formulated as the statistical hypothesis determine whether or not to accept an input pattern by comparing the likelihood ratio of HMM and anti-models to a critical threshold. It is quite difficult to fix a threshold for the probability of a HMM because the range of such probabilities varies severely depending on the chosen class model. We estimate the critical threshold, which is very class-dependent, using the likelihood scores for the training database. In our experiments, we applied the proposed estimating method of the threshold to the HMM based 3D hand gesture recognition system. We found that this method can be used successfully for rejecting unreliable input gestures regardless of the types of anti-models.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.1-10
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• 2010

As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.609-614
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• 2014

Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Recent studies have validated the age-old technique of employing motor imagery training (mental rehearsal of a movement) to boost motor performance in athletes, much as a champion downhill skier visualizes the course prior to embarking on a run. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a "backdoor" to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.