• 아동학회지
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• 제37권2호
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• pp.1-11
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• 2016

Objective: This study examined how child care teachers' playfulness and recognition of music and movement relate to their teaching intention of music and movement. Methods: Participants were 200 child care teachers in Seoul, Incheon and Gyeonggi areas. The data were analyzed for descriptive statistics, pearson's correlation analysis, hierarchical multiple regression analysis, and sobel test. Results: The main results were as follows: First, child care teachers' playfulness, teaching intention of music and movement and their recognition of music and movement were positively correlated. Second, child care teachers' playfulness influenced on their teaching intention of music and movement. Finally, teachers' recognition of music and movement mediated the relationship between teachers' playfulness and their teaching intention of music and movement. Conclusion: This study showed that teachers' playfulness influenced on their positive recognition of music and movement activities, which was the variable that caused mediation in the teachers' playfulness and their teaching attention.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.367-372
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• 2021

The purpose of this study is to suggest that the movement expression activity of intellectually disabled people is effective in the learning process of LMA motion recognition based on Kinect sensor. We performed an ICT motion recognition games for intellectually disabled based on movement learning of LMA. The characteristics of the movement through Laban's LMA include the change of time in which movement occurs through the human body that recognizes space and the tension or relaxation of emotion expression. The design and implementation of the motion recognition model will be described, and the possibility of using the proposed motion recognition model is verified through a simple experiment. As a result of the experiment, 24 movement expression activities conducted through 10 learning sessions of 5 participants showed a concordance rate of 53.4% or more of the total average. Learning motion games that appear in response to changes in motion had a good effect on positive learning emotions. As a result of study, learning motion games that appear in response to changes in motion had a good effect on positive learning emotions

• 전기학회논문지
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• 제63권6호
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• pp.813-819
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• 2014

The purpose of this study was to extract accurate parameters of facial movement features using 3-D motion capture system in speech recognition technology through lip-reading. Instead of using the features obtained through traditional camera image, the 3-D motion system was used to obtain quantitative data for actual facial movements, and to analyze 11 variables that exhibit particular patterns such as nose, lip, jaw and cheek movements in monosyllable vocalizations. Fourteen subjects, all in 20s of age, were asked to vocalize 11 types of Korean vowel monosyllables for three times with 36 reflective markers on their faces. The obtained facial movement data were then calculated into 11 parameters and presented as patterns for each monosyllable vocalization. The parameter patterns were performed through learning and recognizing process for each monosyllable with speech recognition algorithms with Hidden Markov Model (HMM) and Viterbi algorithm. The accuracy rate of 11 monosyllables recognition was 97.2%, which suggests the possibility of voice recognition of Korean language through quantitative facial movement analysis.

• 한국콘텐츠학회논문지
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• 제14권1호
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• pp.24-29
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• 2014

본 논문에서는 키넥트 적외선 프로젝터를 통해 깊이를 감지할 수 있는 카메라를 이용하여 사람 움직임을 추적하고 본 논문에서 제안한 몸동작 모델 인식을 통하여 3D 콘텐츠를 제어하는 기법을 제안 한다. 본 논문에서 제안하는 사람의 동작 인식 모델은 사람의 오른팔과 왼팔의 손목, 팔꿈치, 어께 움직임의 거리를 계산하여 좌, 우, 상, 하, 확대, 축소, 선택 등의 7가지 동작 상태를 인식한다. 본 연구에서 제안한 키넥트 기반의 동작 인식 모델은 기존의 접촉식 방식의 인터페이스와 비교할 때 특정센서 또는 장비 부착에 대한 불편함을 없애고 고비용의 하드웨어 시스템을 이용하지 않음으로서 사람의 자연스런 몸동작 이동에 따른 저 비용 3D 콘텐츠 제어 기술을 보여준다.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• 한국콘텐츠학회논문지
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• 제13권12호
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• pp.672-679
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• 2013

창의성은 문제인식과 해결방법으로 상상력을 통한 새로운 이미지의 사고능력과 표현이다. 이 연구는 신체움직임의 창의성이론을 탐구하고 창의성 요인을 분석하였다. 연구결과, 신체움직임의 창의성은 첫째, 움직임 자각 둘째, 신체움직임 디자인 셋째, 움직임의 발견, 넷째, 움직임활용이라는 단계가 필요하다. 자기지각과 자아개념을 통한 새로운 이미지의 활용은 문제인식과 해결기능에 대한 창의적인 향상을 가져온다. 결론적으로 신체움직임의 창의성은 상호작용에 의한 '제3의 힘'과 '흐름의 유연성'으로 신체움직임의 무한성을 의미한다.

• 융합신호처리학회논문지
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• 제11권4호
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• pp.289-297
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• 2010

본 논문에서는 음성인식을 위한 음성구간 검출과정에서 유입될 수 있는 동적인 음향에너지 이외에 화자의 입술움직임 영상신호까지 확인함으로써 외부 음향잡음이 음성인식 대상으로 오인식되는 것을 방지하기 위한 한 가지 방법이 제시된다. 우선, 연속적인 영상이 PC용 영상카메라를 통하여 획득되고 그 입술움직임 여부가 식별된다. 다음으로, 입술움직임 영상신호 데이터는 공유메모리에 저장되어 음성인식 프로세서와 공유한다. 한편, 음성인식의 전처리 단계인 음성구간 검출과정에서 공유메모리에 저장되어진 데이터를 확인함으로써 화자의 발성에 의한 음향에너지인지의 여부가 입증된다. 최종적으로, 음성인식기와 영상처리기를 연동시켜 실험한 결과, 영상카메라에 대면해서 발성하면 음성인식 결과의 출력에 이르기까지 연동처리가 정상적으로 진행됨을 확인하였고, 영상카메라에 대면치 않고 발성하면 연동처리시스템이 그 음성인식 결과를 출력치 못함을 확인하였다. 또한, 오프라인하의 입술움직임 초기 특정값 및 템플릿 초기영상을 온라인하에서 추출된 입술움직임 초기특정값 및 템플릿 영상으로 대체함으로써 입술움직임 영상 추적의 변별력을 향상시켰다. 입술움직임 영상 추적과정을 시각적으로 확인하고 실시간으로 관련된 패러미터를 해석하기 위해 영상처리 테스트베드를 구축하였다, 음성과 영상처리 시스템의 연동결과 다양한 조명환경 하에서도 약 99.3%의 연동율을 나타냈다.

• 한국컴퓨터정보학회논문지
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• 제24권6호
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• 한국IT서비스학회지
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• 제20권6호
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• pp.45-62
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• 2021

After the COVID-19 outbreak in 2019, the spread of COVID-19 has not been easily caught despite preventive measures in each country. The spread of COVID-19 has hit the world, especially in the economic and tourism sectors. Countries around the world are easing restrictions on the movement of vaccinated people in preparation for the post-corona era. Under the name of "Vaccine Passport," "Vaccination Certificate," and "Digital Health Pass," vaccination measures are being implemented to allow vaccination recipients to use multi-use facilities. However, there is no international agreement on the movement of countries, and each country has its own immigration policy. In order to return to pre-corona daily life, global agreements must be reached from the movement of vaccinated people between countries, and standards and implementation methods must be determined. This study focuses on the implementation and utilization of vaccination certificates suitable for the COVID-19 era. We will look at the spread of COVID-19 and its international response policies. In the case of COVID-19, we will investigate why vaccination certificate installation should be standardized and how far the current standardization has been discussed, and discuss the characteristics of vaccination certificate installation and considerations. In order for the immunization certificate discussed in the previous chapter to be recognized internationally, institutional and technical considerations are identified and security factors that may occur in each implementation are also presented. Finally, the international recognition case of vaccination certificate is discussed, and the method of installation and utilization of vaccination certificate is proposed. This paper can be used as a policy because of its timeliness in studying the standards of vaccination certificates and considerations for international recognition to restore movement between countries in the spread of COVID-19. In addition, if other infectious diseases occur in the future or similar cases where movement between countries is restricted, it can be used as a reference to support the movement of verified people.

• International Journal of Contents
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• 제16권3호
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• pp.1-17
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• 2020

Human motion recognition is essential for user-centric services such as surveillance-based security, elderly condition monitoring, exercise tracking, daily calories expend analysis, etc. It is typically based on the movement data analysis such as the acceleration and angular velocity of a target user. The existing motion recognition studies are only intended to measure the basic information (e.g., user's stride, number of steps, speed) or to recognize single motion (e.g., sitting, running, walking). Thus, a new mechanism is required to identify the transition of single motions for assessing a user's consecutive motion more accurately as well as recognizing the user's body and surrounding situations arising from the motion. Thus, in this paper, we collect the human movement data through Android smartphones in real time for five targeting single motions and propose a mechanism to recognize a consecutive motion including transitions among various motions and an occurred situation, with the state transition model to check if a vulnerable (life-threatening) condition, especially for the elderly, has occurred or not. Through implementation and experiments, we demonstrate that the proposed mechanism recognizes a consecutive motion and a user's situation accurately and quickly. As a result of the recognition experiment about mix sequence likened to daily motion, the proposed adoptive weighting method showed 4% (Holding time=15 sec), 88% (30 sec), 6.5% (60 sec) improvements compared to static method.