• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.478-484
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• 2018

The choice of the motion features influences the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of the human body, environment and video camera. So the accuracy of action recognition is restricted. On the bases of studying the representation and recognition of human actions, and giving fully consideration to the advantages and disadvantages of different features, the Dense Trajectories(DT) algorithm is a very classic algorithm in the field of behavior recognition feature extraction, but there are some defects in the use of optical flow images. In this paper, we will use the improved Dense Trajectories(iDT) algorithm to optimize and extract the optical flow features in the movement of human action, then we will combined with Support Vector Machine methods to identify human behavior, and use the image in the KTH database for training and testing.

• ETRI Journal
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• v.40 no.4
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• pp.511-521
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• 2018

The ability to realize human-motion imitation using robots is closely related to developments in the field of artificial intelligence. However, it is not easy to imitate human motions entirely owing to the physical differences between the human body and robots. In this paper, we propose a work chain-based inverse kinematics to enable a robot to imitate the human motion of upper limbs in real time. Two work chains are built on each arm to ensure that there is motion similarity, such as the end effector trajectory and the joint-angle configuration. In addition, a two-phase filter is used to remove the interference and noise, together with a self-collision avoidance scheme to maintain the stability of the robot during the imitation. Experimental results verify the effectiveness of our solution on the humanoid robot Nao-H25 in terms of accuracy and real-time performance.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1777-1778
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• 2007

In this paper, We design and implement a humanoid robot, With Educational purpose, which can collaborate and communicate with human. We present an affective human-robot communication system for a humanoid robot, D2, which we designed to communicate with a human through dialogue. D2 communicates with humans by understanding and expressing emotion using facial expressions, voice, gestures and posture. Interaction between a human and a robot is made possible through our affective communication framework. The framework enables a robot to catch the emotional status of the user and to respond appropriately. As a result, the robot can engage in a natural dialogue with a human. According to the aim to be interacted with a human for voice, gestures and posture, the developed Educational humanoid robot consists of upper body, two arms, wheeled mobile platform and control hardware including vision and speech capability and various control boards such as motion control boards, signal processing board proceeding several types of sensors. Using the Educational humanoid robot D2, we have presented the successful demonstrations which consist of manipulation task with two arms, tracking objects using the vision system, and communication with human by the emotional interface, the synthesized speeches, and the recognition of speech commands.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.2
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• pp.211-223
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• 2018

In global apparel product development, flat is one of the most important key factor for technical design communication. Proportionally correct flats based on correct scaled human body figures are imperative to be successful in the fashion business. In this study the researchers were to develop body templates for flats for Korean women body types using data from 'Size Korea 2004 (5th)', which is a Korean government apparel sizing project to analyze women's body measurements (age range 7-49). We measured 13 height measurements, 6 width measurements, 8 circumference measurements, 6 length measurements, 3 angle measurements and 5 body measurements. A body figure (i.e., schema) for each group was created by Pattern Design Software (PAD) System 4.1. Muscle was added to the schema created by Adobe Illustrator to ensure a better visualization and convenience for industry uses for flats. Developed body figure template of representative type had the largest difference in height level compared to exiting figures. It had a bigger head, lower crotch level, and longer crotch depth and hip length than existing figures.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.104-108
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• 2014

The field of body sensor networks has attracted interest of many researchers due to its potential to revolutionize medicine. These sensors are usually implanted inside the human body and communicate among themselves. In the process of receiving, processing, or transmitting data, these devices produce heat. This heat damages the tissues surrounding the devices in the case of prolonged exposure. In this paper, to reduce this damages, we have improved and evaluated two protocols-the least temperature routing protocol and adaptive least temperature routing protocol-by implementing clustering as well as a leadership rotation algorithm. We used Castalia to simulate a basic body area network cluster composed of 6 nodes. A throughput application was used to simulate all the nodes sending data to one sink node. Simulations results shows that improved communication protocol with leadership rotation algorithm significantly reduce the energy consumption as compared to a scheme without leadership rotation algorithm.

• Journal of the Korean Society of Costume
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• v.31
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• pp.5-16
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• 1997

This paper studies in terms of nonverbal communication the roles of Gut-clothinbgs used in Jin-Do Sit-gim Gut are classified as follows: 1) The message communicated through the ordinary clothings of a shaman is that he or she is waiting to serve as a presider of a Gut ceremony actiong as a mediator between the spirtual and the human world. 2) The shaman clothings representing many kinds of spirits are visualized figures which are closely related to the common wishes of most people in society e. g. physical and material well-being longevity fertility. 3) The clothings serve as a body figure in the Gut are classified into 5 groups. (1) Laid-on clothings give the message that the body is standing still. (2) Wrapped clothings serve as an incarnated body of the dead. (3) Spread clothings represent a lying body. (4) Oscillated clothings are the symbols of a spirit which moves from this world to another. (5) Burned clothings mean that the spirit has attained a complete seperation from this world.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.263-267
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• 2015

current mine detector can't division the section if it is conducted and it needs too much labor force and time. in addition to, if the user don't move the head of sensor in regular speed or move it too fast, it is hard to detect a mine exactly. according to this, to improve the problem using one direction ultrasonic wave sensing signal, that is made up of human body antenna part, main micro processor unit part, smart glasses part, body equipped LCD monitor part, wireless data transmit part, belt type power supply part, black box type camera, Security Communication headset. the user can equip this at head, body, arm, waist and leg in removable type. so it is able to detect the powder in a 360-degree on(under) the ground whether it is metal or nonmetal and it can express the 2D or 3D film about distance, form and material of the mine. so the battle combats can avoid the mine and move fast. also, through the portable battery and twin self power supply system of the power supply part, combat troops can fight without extra recharge and we can monitoring the battle situation of distant place at the command center server on real-time. and then, it makes able to sharing the information of battle among battle combats one on one. as a result, the purpose of this study is researching a smart wearable mine detector which can establish a smart battle system as if the commander is in the site of the battle.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.38-44
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• 2007

This paper presented a location and attitude estimation scheme of a capsule endoscope based on ultrasonic ranging. The scheme comprised eight on-capsule ultrasonic sensors to alleviate measurement errors due to irregularities in human body ultrasonic characteristics. It calculated the coordinate values and angles in a Cartesian coordinate system. The Matlab simulation reflecting random errors yielded the average deviations of 0.8mm in the location and $0.2^{\circ}$ in the attitude angle. These values are far smaller than normal intestine movement ranges inside human body, and will contribute accurate diagnosis of intestine.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.2
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• pp.133-143
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• 2012

The study on social robots has been actively conducted in the robot research community. In the area of robot design, however, there are few studies regarding robot motions that are one of the methods for interaction between humans and robots. This is a preliminary study to find preferred human motions that can be applied to social robots. We conducted a two-phased empirical study about preferred human motions. In the first phase, four representative human motions, such as 'greeting', 'I don't know', 'positive answer', and 'giving', were captured through 28 body makers and video recording. 10 young and 6 elderly Singaporeans participated in the motion capture process. In the second phase, the communication efficiency, emotion, and satisfaction of the human motions recorded in the first phase were measured by a questionnaire and 31 young Koreans, 35 young Singaporeans participated to investigate cultural differences. We drew the conclusion that motions used in the same culture are efficient in communication and also give friendliness and satisfaction. In addition, regardless of user's culture, young people's motions and female motions were preferred in terms of communication efficiency, emotional aspect, satisfaction.