• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.34-38
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• 2002

A virtual human which can evaluate Kansei such as comfort, pain, etc. when the virtual human uses some product is developed. In this paper, method of the evaluation of Kansei by the virtual human is presented. The body of our virtual human is modeled as an uniform non-linear elastic one with a skeleton. The deformation of the body on the contact with some product is simulated using a FEM analysis, and by using of the simulated results (load distribution, strain, etc.) on the contact surface the Kansei is predicted. As examples of the application, comfort of buttocks on seating and pain of arm on hanging of bag are shown. This virtual human can apply for the design of virtual products and also the simulation of medical care.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.186-192
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• 2009

In this paper, we represent the recognition method for human frontal upper body pose. In HCI(Human Computer Interaction) and HRI(Human Robot Interaction) when a interaction is established the human has usually frontal direction to the robot or computer and use hand gestures then we decide to focus on human frontal upper-body pose, The two main difficulties are firstly human pose is consist of many parts which cause high DOF(Degree Of Freedom) then the modeling of human pose is difficult. Secondly the matching between image features and modeling information is difficult. Then using Pictorial Model we model the human main poses which are mainly took the space of frontal upper-body poses and we recognize the main poses by making main pose database. using determined main pose we used the model parameters for particle filter which predicts the posterior distribution for pose parameters and can determine more specific pose by updating model parameters from the particle having the maximum likelihood. Therefore based on recognizing main poses and tracking the specific pose we recognize the human frontal upper body poses.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.113-121
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• 2020

Human Pose Estimation (HPE) which localizes the human body joints becomes a high potential for high-level applications in the field of computer vision. The main challenges of HPE in real-time are occlusion, illumination change and diversity of pose appearance. The single RGB image is fed into HPE framework in order to reduce the computation cost by using depth-independent device such as a common camera, webcam, or phone cam. However, HPE based on the single RGB is not able to solve the above challenges due to inherent characteristics of color or texture. On the other hand, depth information which is fed into HPE framework and detects the human body parts in 3D coordinates can be usefully used to solve the above challenges. However, the depth information-based HPE requires the depth-dependent device which has space constraint and is cost consuming. Especially, the result of depth information-based HPE is less reliable due to the requirement of pose initialization and less stabilization of frame tracking. Therefore, this paper proposes a new method of HPE which is robust in estimating self-occlusion. There are many human parts which can be occluded by other body parts. However, this paper focuses only on head self-occlusion. The new method is a combination of the RGB image-based HPE framework and the depth information-based HPE framework. We evaluated the performance of the proposed method by COCO Object Keypoint Similarity library. By taking an advantage of RGB image-based HPE method and depth information-based HPE method, our HPE method based on RGB-D achieved the mAP of 0.903 and mAR of 0.938. It proved that our method outperforms the RGB-based HPE and the depth-based HPE.

• Journal of Fashion Business
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• v.5 no.5
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• pp.7-15
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• 2001

As a means of achieving fashion technology and scientification, this research on the standardization proposals of body type research methods has the following conclusions: 1. As human body displays different characteristics according to races, regions, sexes, and ages, clothing products (unlike other industrial goods) cannot be subject to global standardization. As a result, clothing size standardization can be desirably regionalized, for example, as Asian, European countries, etc. 2. In order to share human-body-concerned information among nations, programs for raw data exchange need to be urgently developed. 3. Top priority is databasing all raw data at home and abroad. 4. So that the findings of body type research can be practically applied to the concerned industry, industry-academy cooperation and information exchange are a must. While researchers have to heighten the precision of their studies, industrial partners ought to focus on the invaluable importance of academic research. 5. The scientific body type analysis, the basis of fashion technology, as well as the development of its application technology and software are ultimately and urgently required.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.109-116
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• 2016

Sensing module of standing and moving human body using shutter method was developed. The module consists of Fresnel lens, pyroelectric infrared (PIR) sensor, interface circuit of the PIR, micro control unit(MCU), and alarm light emitting diode(LED). The principle for standing human body is chopping the thermal of human body using camera shutter. The human sensing signal in MCU by algorithm of interrupt function is detected. By unifying an apparatus and print circuit board(PCB), the developed module can be replaced as commercial moving human body detector. Experiment results show that sensing distance is about 7.0m and sensing angles is about $110^{\circ}$ at room temperature. In these condition, sending ratio was 100% and the power dissipation of the module was 100mW.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.719-722
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• 2009

The purpose of this paper is to develop a robot that moves independently, communicates with a human, and explicitly extracts information from the human mind that is rarely expressed verbally. In a spoken dialog system for information collection, it is desirable to continue communicating with the user as long as possible, but not if the user does not wish to communicate. Therefore, the system should be able to terminate the communication before the user starts to object to using it. In this paper, to enable the construction of a decision model for a system to decide when to stop communicating with a human, we acquired speech and motion data from individuals who were asked many questions by another person. We then analyze their speech and body motion when they do not mind answering the questions, and also when they wish the questioning to cease. From the results, we can identify differences in speech power, length of pauses, speech rate, and body motion.

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.103-111
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• 2007

The purpose of this study is to categorize and analyze the body shape of obese Korean men that are needed for industrial design. Using the anthropometric data that were surveyed through the 5^th Size Korea project, this study was conducted in four steps mostly through the multivariate statistical analysis. In the first step, Broca, BMI, WHR indices are used to define obesity and select obese men from Korean adults and teens. After 34 human anthropometric variables are supposed to be related to obesity were extracted through an expect survey. In the second step, a factor analysis was executed for those human anthropometric variables. Through this analysis, we obtained the human body factors that are related to the representation of obesity. Then the third step, we used a cluster analysis from the result of the factor analysis. And ANOVA analysis was also conducted to obtain the critical obese human anthropometric variables. In the final step, we found the characteristics of the body types of obese men according to clusters and ages. The body types of obese men classified in the study are expected to be applied to product design for clothing, furniture, automobile packaging, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.465-469
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• 2017

In this paper we propose a human body tracking method for application of smartphones. The conventional human body tracking method is divided into a sensor-based method and a vision-based method. The sensor-based methods have a weakness in that tracking accuracy is low due to cumulative error of position information. The vision-based method has no cumulative error, but it requires reduction of the computational complexity for application of smartphone. In this paper we use the improved HOG algorithm as a human body tracking method for application of smartphone. The improved HOG algorithm is implemented through downsampling and frame sampling. Gaussian pyramid is applied for downsampling, and uniform sampling is applied for frame sampling. We measured the proposed algorithm on two devices, four resolutions, and four frame sampling intervals. We derive the best detection rate among downsampling and frame sampling parameters that can be applied in realtime.

• Journal of the Korean Home Economics Association
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• v.23 no.2
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• pp.13-19
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• 1985

While the appearance of new textiles and processing materials results in the improvement in quality of clothes and its luxury, a question about the irritation of clothes on the human body must be raised. In Japan and many countries in Europe, they are searching for a countermeasure against the bad influence of clothes on the human body for the purpose of protecting consumers. In our country, a little bit of study about the skin irritatio has been carried out. In this thesis, the literature on the kinds of the irritation of clothes on the human body was studied and analysed. And then I arranged it from the view-point of clothing hygienics. For example, we should observe the legal regulations and the administrative control in the process of production and distributive management of clothes for our safety. Therefore the authorities concerned must have preparations for the safety and this monograph is going to give information for it.