• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.73-78
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• 2021

As interest in beauty has increased, various studies have been conducted, and related companies have considered the anthropometric data handled between humans and interfaces as an important factor. However, owing to the nature of 3D human body scanners used to extract anthropometric data, it is difficult to accurately analyze a user's body shape until a service is provided because the user only scans and extracts data. To solve this problem, the body shape of several users was analyzed, and the collected anthropometric data were obtained using a 3D human body scanner. After processing the extracted data and the anthropometric data, a custom deep learning model was designed, the designed model was learned, and the user's body shape information was predicted to provide a service suitable for the body shape. Through this approach, it is expected that the user's body shape information can be predicted using a 3D human body scanner, based upon which a beauty service can be provide.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.227-232
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• 2016

3D body scan data are used widely in various fields to make products and living spaces for superior human body fitness. Based on the 3D measurements of human bodies for teens in Size Korea 2013, this research provides a way of finding the representative body sizes and 3D body scan data. First, a multi-dimensional vector space consisting of many measurement items was projected onto a 2D vector space with circumference and length components via factor analysis. The representative body sizes and 3D scan data close to these values were obtained via the Mahalanobis distance in 2D space. Considering the adolescent growth pattern shown on this 2D space, males were divided into 4 age groups and females were divided into 3 age groups. Using the eigenbodies corresponding to the column vectors of the component score coefficient matrix, the representative body sizes of 13 measurement items (male) and 14 measurement items (female) for each age group were calculated. The representative body sizes and 3D scan data are very useful for modeling representative 3D human figures.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.595-606
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• 2020

This study develops an optimal two-dimensional (2D) pattern from three-dimensional human scan data by considering the cycling posture and dermatome of high school male cyclists. By analyzing the body surface change in the cycling posture and considering the dermatome of the lower limbs, the optimal cutting line setting and the development of cycling tights for individual cyclists were presented to provide data that could be used in the clothing industry. We designed three cycling tights to solve the size unsuitability. 3D design 1 is a non-extension design based on the analysis of the 3D human body scan data, in which parts were connected diagonally from the front of the knee to the back of the knee. 3D design 2 removed both the front and back to reduce air resistance during cycling. 3D design 3 did not have a cutting line on the front panel because of the air resistance during cycling in the front area. We analyzed the garment pressure for 8 points of lower body and performed a subjective evaluation of the 3D designed tights and the current cycling tights. The 3D design 1 in this study was well received in the omphalion, thigh, and hip area, while 3D design 3 was well received in the omphalion, thigh, hip, and bottom bands. Therefore, the LoNE of 3D design 1 was applied to the front, and the hip cutting line of 3D design 3 was applied to the back.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.383-383
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• 2000

In this paper, a motion adaptation control is applied for animation of 3-D human character. The method includes parameterization of joint motion data, motion adaptation based on body ratio of character, dynamic adaptation using genetic algorithm, etc. The feasibility of motion adaptation technique is verified by applying to motion control and adaptation of a 3-D human character.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2042-2059
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• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.10
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• pp.796-800
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• 2009

Currently, there are many software tools that can generate 3D human figure models and animations based on the advancement of computer graphics technology. However, we still have problems in interoperability of human data models in different applications because common data models do not exist. To address this issue, the Web3D Consortium and the ISO/IEC JTC1 SC24 WG6 have developed the H-Anim standard. However, H-Anim does not include human motion data formats although it defines the structure of a human figure. This research is intended to obtain interoperable human animation by defining the data for human motions in H- Anim figures. In this paper, we describe a syntactic method to define motion data for the H-Anim figure and its implementation. In addition, we describe a method of specifying motion parameters necessary for generating animations by using an arbitrary character model data set created by a general graphics tool.

• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.1-11
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• 2022

The Skinned Multi-Person Linear Model (SMPL) is the most widely used parametric 3D Human Model optimized and learned from CAESAR, a 3D human scanned database created with measurements from 3,800 people living in United States in the 1990s. We point out the lack of racial diversity of body types in SMPL and propose K-SMPL that better represents Korean 3D body shapes. To this end, we develop a fitting algorithm to estimate 2,773 Korean 3D body shapes from Korean body measurement data. By conducting principle component analysis to the estimated Korean body shapes, we construct K-SMPL model that can generate various Korean body shape in 3D. K-SMPL model allows to improve the fitting accuracy over SMPL with respect to the Korean body measurement data. K-SMPL model can be widely used for avatar generation and human shape fitting for Korean.

• Fashion & Textile Research Journal
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• v.13 no.6
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• pp.966-971
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• 2011

This study is designed to develop programs that analyze the distance of clothes from human skin and cross-sectional body figures based on 3D human body scan data, and to verify accuracy and efficiency of the program so that it can be used for clothing fit evaluation and 3D human body research. The auto cross-sectional imaging program was developed by using Visual C++ and OpenGL, and the 3D human body scan data were adopted to measure the space between skin and clothing. The space measurements were obtained by two widely used programs, RapidForm and AutoCAD, and a program devised by the researchers of this study. Measuring time and space measurements from different programs were compared in order to verify accuracy and efficiency of the newly-devised program. As a result, no significant difference was found in the measurements. However, the required time to measure one cross section was different within the significance level of 0.05, and the differences become more remarkable as the number of measuring and the angle of space between skin and clothing increase. Therefore, the program developed by this study is expected to be useful for research on body shapes and fit evaluation based on 3D human body scan data in the fashion field.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.844-855
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• 2005

This paper proposes a human action recognition scheme for Intelligent Web Browser. Based on the principle that a human action can be defined as a combination of multiple articulation movements, the inference of stochastic grammars is applied to recognize each action. Human actions in 3 dimensional (3D) world coordinate are measured, quantized and made into two sets of 4-chain-code for xy and zy projection planes, consequently they are appropriate for applying the stochastic grammar inference method. We confirm this method by experiments, that various physical actions can be classified correctly against a set of real world 3D temporal data. The result revealed a comparatively successful achievement of $93.8\%$ recognition rate through the experiments of 8 movements of human head and $84.9\%$ recognition rate of 60 movements of human upper body. We expect that this scheme can be used for human-machine interaction commands in a web browser.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.157-166
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• 2006

The human body, which is composed of concave and convex curvatures, makes it difficult to transfer into 2D patterns directly from 3D data. In previous studies. Jeong, et al.(2004) suggested the block method was fester and easier when dealing with the triangular patches of male's upper dress form. Although the block method is useful to make a pattern, the information(area, length, etc.) from a 2D pattern would be different depending on the direction of the block method. As a result horizontal and diagonal block methods were suggested as optimal methods for 2D tight-fitting patterns. These block methods were closer to the original area of the 3D scan data than the vertical block method. The total area of the 2D pattern obtained by the horizontal and diagonal block methods showed little differences. In case of the horizontal and diagonal block methods, the total error of the 2D pattern area ranged from $0.01\%\~0.25\%$. In comparing the length of the 2D pattern with that of the 3D scan data, the obtained 2D pattern was $0.1\~0.2cm$ shorter than the 3D scan data, which was within the acceptable range of errors in making clothes. 3D space distribution images between the body surface and the experimental clothing were also measured and $3\%$ enlargement of the original pattern was verified as the adequate adjustment.