• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.122-129
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• 2020

The circumference of the body is not only an indicator in order to buy clothes in our life but an important factor which can increase the effectiveness healing properly after figuring out the shape of body in a hospital. There are several measurement tools and methods so as to know this, however, it spends a lot of time because of the method measured by hand for accurate identification, compared to the modern advanced societies. Also, the current equipments for automatic body scanning are not easy to use due to their big volume or high price generally. In this papers, OpenPose model which is a deep learning-based Skeleton Tracking is used in order to solve the problems previous methods have and for ease of application. It was researched to find joints and an approximation by applying the data of the deep camera via reference data of the measurement parts provided by the hospitals and to develop a program which is able to measure the circumference of the body lighter and easier by utilizing the elliptical circumference formula.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.209-218
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• 2013

Early researches in human action recognition have focused on tracking and classifying articulated body motions. Such methods required accurate segmentation of body parts, which is a sticky task, particularly under realistic imaging conditions. Recent trends of work have become popular towards the use of more and low-level appearance features such as spatio-temporal interest points. Given the great progress in pose estimation over the past few years, redefined views about pose-based approach are needed. This paper addresses the issues of whether it is sufficient to train a classifier only on low-level appearance features in appearance approach and proposes effective pose-based approach with pose estimation for emotional action recognition. In order for these questions to be solved, we compare the performance of pose-based, appearance-based and its combination-based features respectively with respect to scenario of various emotional action recognition. The experiment results show that pose-based features outperform low-level appearance-based approach of features, even when heavily spoiled by noise, suggesting that pose-based approach with pose estimation is beneficial for the emotional action recognition.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.255-262
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• 2012

Human motion tracking algorithm is receiving attention from many research areas, such as human computer interaction, video conference, surveillance analysis, and game or entertainment applications. Over the last decade, various tracking technologies for each application have been demonstrated and refined among them such of real time computer vision and image processing, advanced man-machine interface, and so on. In this paper, we introduce cost-effective and real-time human motion tracking algorithms based on depth image 3D point matching with a given superellipsoid body representation. The body representative model is made by using parametric volume modeling method based on superellipsoid and consists of 18 articulated joints. For more accurate estimation, we exploit initial inverse kinematic solution with classified body parts' information, and then, the initial pose is modified to more accurate pose by using 3D point matching algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.107-112
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• 2005

In this study, the dynamic analysis is performed fur predicting the transmitted force to flexible human body induced by prototype HIF(High Impulsive force) device operation, which is partially assembled by major parts. A beam-mass model and a shear-structure model are used for the flexible mount structure and their dynamic behavior are investigated by experimental results under rigid/flexible mount conditions using a general purpose device. From the test result of prototype device in rigid mount condition, the transmitted force to human body which can not be measured directly, is estimated based on the proved mount structure model.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.85-92
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• 2017

Recently, in the field of video surveillance, a Deep Learning based learning method has been applied to a method of detecting a moving person in a video and analyzing the behavior of a detected person. The human activity recognition, which is one of the fields this intelligent image analysis technology, detects the object and goes through the process of detecting the body keypoint to recognize the behavior of the detected object. In this paper, we propose a method for Body Keypoint Localization based on Object Detection using RGB-D information. First, the moving object is segmented and detected from the background using color information and depth information generated by the two cameras. The input image generated by rescaling the detected object region using RGB-D information is applied to Convolutional Pose Machines for one person's pose estimation. CPM are used to generate Belief Maps for 14 body parts per person and to detect body keypoints based on Belief Maps. This method provides an accurate region for objects to detect keypoints an can be extended from single Body Keypoint Localization to multiple Body Keypoint Localization through the integration of individual Body Keypoint Localization. In the future, it is possible to generate a model for human pose estimation using the detected keypoints and contribute to the field of human activity recognition.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.11
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• pp.1507-1519
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• 2005

The purpose of this study was to compare two methods of measuring body surface area (BSA). The BSA of Korean adults was measured using both three-dimensional (3D) scanning and an alginate method. Two males (one overweight and one lean) and one overweight female participated as subjects. The results were as follows: First, the 3D scanned BSA of all three subjects was smaller than the BSA measured using the alginate method by as much as $6-14\%$. The difference in methods was greater in the overweight participants than in the lean subject. Second, the results comparing the BSA obtained using these two methods and the BSA estimated by 10 previously developed formulas, showed that the 3D scanned BSA was the smallest among the 12 BSAs. Third, in comparing the regional differences between these two methods, the regional BSA of the lean subject (male 2) did not show any significant difference, but the overweight subjects (male 1, female 1) showed a significant difference. Forth, the biggest difference in regional BSA obtained through these two methods was in the hand, for all three subjects. The 3D scanned hand surface area was smaller than the hand surface area measured by the alginate method by as much as $24-34\%$. Fifth, in the percentage of regional BSA, there was no significant difference in these two methods. The reasons for the underestimation in the 3D scanning might be because: 1) the 3D scanner can not recognize the folding and shading of body parts, such as the finger, toe, ear, armpit, crotch and breast, 2) 3D patching and smoothing processes depend on researchers. However, the 3D scanning method is applicable to the estimation of the entire BSA, if the surface area of the hands is known, and the participant is not overweight.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.213-220
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• 2002

Anthropometric survey is important as a basis for human engineering fields. According to our experiences, there are difficulties in obtaining the measurements of some body parts because respondents are reluctant to expose. In order to overcome these difficulties, we propose a method for estimating such hard-to-measure measurements by using easy-to-measure measurements those are closely related to them. Multiple Regression Model, Feedforward Neural Network(FNN) Model and Projection Pursuit Regression(PPR) Model will be used as analytical tools for this purpose. The method we propose will be illustrated with real data from the 1992 Korea national anthropometric survey.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.5
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• pp.44-53
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• 1993

In this paper, we discuss on the control algorithm to make the wheeled inverse pendulum type mobile robot move in two dimensional plane. The robot considered in this paper has two independently driven wheels in same axel which suport and move it-self, and is assumed to have the fyro type sensor to know the inclination algle of the body and rotary encoders to know wheel's rotation angular velocity. The control algorithm is divided into three parts. The first part is for the posture and velocity control for forward-backward direction, the second is the steering control, and the last part is for the control of total system to track the given trajectory. We handle the running velocity control of the robot as part of the posture control to keep the balance because the posture relates deeply with the velocity and can be controlled by the velocities of the wheels. The control problem is analyzed as the tracking control, and the controller is realized with the state feedback and feed-forward of the reference velocity. Constructing the control system which contained one intergrator in forward path, we also realized the control system without observer for the estimation of the accumulated errors in the inclination angle of the body. To prevent the robot from being unstable state by sudden variation of the reference velocity when it starts and stops, or changes velocity, the reference velocity of which acceleration is slowly changing, is ordered to the robot. To control its steering, we give the different reference velocities for both wheels which are calculated from the desired angular velocity of the body. Finally, we presents the experimental results of the experimental robot Yamabico Kurara in which the proposed control algorithm had been implemented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.241-246
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• 2001

This paper introduces modeling and solution for the dynamics of pipeline inspection gauge (PIG) flow in natural gas pipeline. Without of bypass flow, the dynamic behavior of the PIG depends on the different pressure between the rear and nose parts, which is generated by injected gas flow behind the tail of the PIG and expelled gas flow in front of its nose. With bypass flow, the PIG dynamics also depends on the amount of bypass flow across its body. The mathematical model are derived for unsteady compressible flow of the PIG driving and expelled gas, and for dynamics of the PIG. The bypass flow is assumed to be incompressible with the condition of its Mach number smaller than 0.45. The method of characteristic (MOC) and the Runge-Kutta method are used to solve the system governing equations. The simulation is performed with a pipeline segment in the Korea Gas Corporation (KOGAS) low pressure system, Ueijungboo-Sangye line. The simulation results show that the derived mathematical model and the proposed solution are effective for estimation the dynamics of the PIG with and without bypass flow under given operational condition.