3D Body Scan Data Research Articles

Development of assessment criteria for elderly lateral torso deformity for 3D scan anthropometry

PurposeWe aimed to establish criteria for determining the deformed lateral torso type to identify individuals requiring measurement methods different from standard methods before extracting dimensions from three-dimensional (3D) scan data.Design/methodology/approachWe collected the 3D body scan data of 119 women aged 70–85 years collected in the 6th Size Korea. Three axes were defined to determine the deformation of the lateral shape, and the angle of each reference axis was used for the analysis. Additionally, to classify the lateral torso shape, 14 experts made visual judgments on the side-view images of the participants.FindingsTo identify the axis that best represented the lateral torso shape, we used each angle value of the three reference axes as an independent variable and the expert’s visual classification as a dependent variable. Each discriminant function was obtained and accuracy calculated. The whole torso axis exhibited the highest accuracy. Next, an assessment scale was developed to determine the shape of the lateral torso using the angular value of the whole torso axis.Originality/valueThe scale developed in this study has the potential to reduce measurement errors arising from elderly deformed torso shapes, thereby enhancing data reliability.

의복설계를 위한 3차원 인체스캔 데이터 미측정 부위 에디팅 방법 비교 연구

The purpose of this research was to propose the most suitable reconstruction method on the missing data at the pate and crotch of the 3D body scan data. After editing the missing data with each of the methods, the anthropometry data gained through the Auto BM(3D automatic measurement program), were compared. As a results of this study indicate that when editing the missing data of the pate, it is effective to use the 'bridge(flat)' function to tidy up the surrounding protruding points and form bridges horizontally and vertically, and then use the 'curvature' function to fill holes. This method is also effective in restoring the round bulging shape of the head, and it is evaluated as effective in recovering the height loss due to missing data. When editing the missing data of the crotch, it was found most effective to form a bridge at the points where the curve occurs in front and behind the crotch, and then use the 'smooth' function to fill in the holes.

Machine learning-based obesity classification considering 3D body scanner measurements

Obesity can cause various diseases and is a serious health concern. BMI, which is currently the popular measure for judging obesity, does not accurately classify obesity; it reflects the height and weight but ignores the characteristics of an individual’s body type. In order to overcome the limitations of classifying obesity using BMI, we considered 3-dimensional (3D) measurements of the human body. The scope of our study was limited to Korean subjects. In order to expand 3D body scan data clinically, 3D body scans, Dual-energy X-ray absorptiometry, and Bioelectrical Impedance Analysis data was collected pairwise for 160 Korean subjects. A machine learning-based obesity classification framework using 3D body scan data was designed, validated through Accuracy, Recall, Precision, and F1 score, and compared with BMI and BIA. In a test dataset of 40 people, BMI had the following values: Accuracy: 0.529, Recall: 0.472, Precision: 0.458, and F1 score: 0.462, while BIA had the following values: Accuracy: 0.752, Recall: 0.742, Precision: 0.751, and F1 score: 0.739. Our proposed model had the following values: Accuracy: 0.800, Recall: 0.767, Precision: 0.842, and F1 score: 0.792. Thus, our accuracy was higher than BMI as well as BIA. Our model can be used for obesity management through 3D body scans.

Anthropometric dataset for the German working-age population using 3D body scans from a regional epidemiological health study and a weighting algorithm

For the ergonomic design of workplaces and products, a representative anthropometric dataset of the working-age population is needed. As body proportions are constantly changing and the latest publicly available dataset for Germany was published in 2004 (data collection period 1999–2002), the aim of this study was to create and publish an updated anthropometric dataset of the German working-age population. Within a regional epidemiological health study, 3D body scan data from 2313 subjects were collected and used to create an anthropometric dataset with a total of 39 ISO 7250-1 measures. To approximate the goal of generating representative values for Germany, the collected regional dataset was weighted with an algorithm, using values from a known nationally representative survey. Based on the weighted dataset, a gender stratified percentile table with values for the 5th, 50th, and 95th percentile was calculated. Practitioner summary: Body proportions are constantly changing and the latest publicly available anthropometric dataset for Germany was published in 2004. A new dataset was created, using 3D body scans from an epidemiological health study and a weighting algorithm. Ultimately, percentile tables with values for the 5th, 50th, and 95th percentile are published.

A Study on the 3D Body Scan Data Editing Process and Errors Analysis for Clothing Design

This study aims to enhance the usage of 3D body scan\ data by proposing a 3D body scan data editing process for clothing design and analyzing factors causing errors by editing processes. The 3D body scan data were collected by using the Body Line Scanner of Hamamatsu, and the configuration of scan data was analyzed by using the RapidForm 2006 program. For the 3D body scan, unmeasured parts necessarily occur, because of the principle of measurement. In addition, some errors are also caused by rotation angles, in developing symmetry for clothing design. Moreover, other errors can occur, in arranging surfaces and editing mesh, for enhancing the quality of 3D body figures. In order to minimize the factors causing such errors, this study suggests a novel 3D body scan editing process consisting of following steps: rotation of scan data, editing of unmeasured parts, arrangement of scan data surfaces, mesh editing of scan data and the horizontal flip of scan data. The findings of this study as basic research for standardizing 3D body scan data and enhancing the quality of scan data are expected to help increase the usage of 3D body scan data.

Prediction of military combat clothing size using decision trees and 3D body scan data

AimTo determine how well decision tree models can predict tailor-assigned uniform sizes using anthropometry data from the New Zealand Defence Force Anthropometry Survey (NZDFAS). This information may inform automatic sizing systems for military personnel. MethodsAnthropometric data from two separate samples of the New Zealand Defence Force military were used. Data on Army personnel from the NZDFAS (n = 583) were used to develop a series of shirt- and trouser-size prediction models based on decision trees. Different combinations of physical, automatic, and post-processed measurements (the latter two derived from a 3D body scan) were trialled, and the models with the highest cross-validation accuracy were retained. The accuracy of these models were then tested on an independent sample of Army recruits (n = 154). ResultsThe automated measurement method (measurements derived automatically by the body scanner software) were the best predictors of shirt size (58.1% accuracy) and trouser size (61.7%), with body weight and waist girth being the strongest predictors. Clothing sizes that were incorrectly predicted by the model where generally one size above or below the tailor-predicted size. ConclusionsAnthropometry measurements, when used with decision tree models, show promise for classifying clothing size. Methodological changes such as fitting gender-specific models, using additional anthropometry variables, and testing other data mining techniques are avenues for future work. More research is required before fully automated body scanning is a viable option for obtaining fast and accurate clothing sizes for military clothing and logistics departments.

Automatic Segmentation and 3D Printing of A-shaped Manikins using a Bounding Box and Body-feature Points

A novel algorithm for 3D-printing technology was proposed to generate large-scale objects, especially A-shaped manikins or 3D human body scan data. Most of the conventional 3D printers have a finite printing volume, and it is the users’ work to convert the target object into a printable size. In this study, an automatic three-step segmentation strategy was applied to the raw manikin mesh data until the final pieces had a smaller size than the 3D printer’s maximum printing volume, which is generally called “beam length”. Human body feature point information was adopted for fashion and textile researchers to easily specify the desired cutting positions. A simple bounding box, especially orienting bounding box, and modified Boolean operator were proposed to extract the specified segments with computational stability. The proposed method was applied to graphically synthesized manikin data, and 1/8, 1/4, and 1/2 scale manikins were successfully printed, minimizing the amount of support structure.

Analysis of EMG Electrode Locations Using 3D Body Scanning for Digital Pattern Construction of a Smart EMG Suit

According to recent trends, smart clothing products that can receive electromyography (EMG) signals during the wearer’s muscle activity are being developed and commercialized. On the other hand, there is a lack of knowledge on the way to specify the electrode locations on the clothing pattern. Accurately located EMG electrodes in the clothing support the reliability and usefulness of the products. Moreover, a systematic process to construct anatomically validated smart clothing digitally should be performed to facilitate the application of a mass-customized manufacturing system. The current study explored the EMG measurement locations of nine muscles and analyzed them in association with various anthropometric points and even postures based on the 3D body scan data. The results suggest that several line segments of the patterns can be substituted by size-dependent equations for the electrodes in place. As a final step, a customized pattern of a smart EMG suit was developed virtually. The current study proposes a methodology to develop body-size dependent equations and patterns of a smart EMG suit with well-located electrodes using 3D scan data. These results suggest ways to produce smart EMG suits in response to impending automation and mass customization of the clothing manufacturing system.

Application Two-Dimensional Pattern Development of Cycling Tights based on the Three-Dimensional Body Scan Data of High School Male Cyclist

This study develops an optimal two-dimensional (2D) pattern from three-dimensional human scan data by con sidering 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 pres sure 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.

Statistical Human Body Shape Model including Elderly People.

In this study, we present a human body shape statistical model including elderly people, which is constructed using principal component analysis (PCA) on 3D body scan data of approximately 130 people. As a pre-process step, a template human body mesh model is fitted to 3D scan data using a coarse-to-fine surface registration technique based on a conformal deformation method, in order to establish correspondences between the scans of different subjects possibly in different poses. To change body style by a small set of parameters, such as "age", "weight" and "height" or the easily measurable anthropometric parameters like "shoulder width", the linear transformations between these attributes and the first 10 principal component scores are obtained. We design a simple user interface to use this deformation model to generate different body styles easily. As a result, we were able to produce and show body styles capturing the characteristics of elderly people whose shoulders fell and back bent. Finally, as an application, we used our deformation method to generate different body types, performed forward dynamics simulations in an assistive device setting and visualized the differences in contact pressure distributions due to body shape changes.

Design in 3D: a computational fashion design protocol

PurposeThe purpose of this study was to create a corset—understructure as well as fabric covering—using only computational, 3D approaches to fashion design. The process incorporated 3D body scan data, parametric methods for the 3D-printed design, and algorithmic methods for the automated, custom-fit fabric pattern.Design/methodology/approachThe methods or protocol-based framework that nucleated this design project (see Figure 1) enabled more concentrated research into the iterative step-by-step procedure and the computational techniques used herein.FindingsThe 3D computational methods in this study demonstrated a new way of rendering the body-to-pattern relationship through the use of multiple software platforms. Using body scan data and computer coding, the computational construction methods in this study showed a pliant and sustainable method of clothing design where designers were able to manipulate the X, Y, and Z coordinates of the points on the scan surface.Research limitations/implicationsA study of algorithmic methods is inherently a study of limitation. The iterative process of design was defined and refined through the particularity of an algorithm, which required thoughtful manipulation to inform the outcome of this research.Practical implicationsThis study sought to illustrate the use and limitations of algorithm-driven computer programming to advance creative design practices.Social implicationsAs body scan data and biometric information become increasingly common components of computational fashion design practices, the need for more research on the use of these techniques is pressing. Moreover, computational techniques serve as a catalyst for discussions about the use of biometric information in design and data modeling.Originality/valueThe process of designing in 3D allowed for the dynamic capability to manipulate proportion and form using parametric design techniques.

Development of helmet mold design system using 3D anthropometric analysis

PurposeThe purpose of this paper is to develop a software can generate helmet mold from three-dimensional (3D) human body scan data.Design/methodology/approachAn algorithm has been developed to divide data into arbitrary number of groups considering the width, length and height of head using the standard normal distribution theory. A basic helmet mold is generated automatically based on the shape of representative convex hull for each group.FindingsIt is possible to analyze the 3D human body scan data of groups with various characteristics and apply them to mass customized production of helmet.Practical implicationsThis methodology can be applied for designing other products related to the head shape such as goggles and masks by varying the measurement items of the head.Social implicationsThis methodology will enable mass customized production centered on consumers in the production and design of various equipment and goods to be worn on the head.Originality/valueAn algorithm has been developed to define the vertex point, which is the limit of scan data, for the analysis of 3D human body scan data scan data. In addition, a system was developed that can mass-produce customized products by effectively dividing groups while taking into account the physical characteristics of consumers.

Developing Fall-impact Protection Pad with 3D Mesh Curved Surface Structure using 3D Printing Technology.

In this study, we present the development of fall-impact protection pads for elderly people using three-dimensional (3D) printing technology. To develop fall-impact protection clothing, it is important to maintain the functionality of the protection pad while ensuring that its effectiveness and appearance remain optimal in the process of inserting it. Therefore, this study explores the benefit of exploiting 3D scan data of the human body using 3D printing technology to develop a fall-impact protection pad that is highly suited to the human body shape. The purpose of this study was to present a 3D modeling process for creating curved protective pads comprising a hexagonal mesh with a spacer fabric structure and to verify the impact protection performance by printing curved pads. To this end, we set up a section that includes pads in the 3D human body scan data and extracted body surface information to be applied in the generation of the pad surface. The sheet-shaped hexagonal mesh structure was cut and separated according to the pad outline, and then deformed according to the curved surface of the human body. The pads were printed, and their protection performance was evaluated; a 79.2–81.8% reduction in impact force was observed compared to similar cases in which the pads were not used.

The Virtual Caliper: Rapid Creation of Metrically Accurate Avatars from 3D Measurements.

Creating metrically accurate avatars is important for many applications such as virtual clothing try-on, ergonomics, medicine, immersive social media, telepresence, and gaming. Creating avatars that precisely represent a particular individual is challenging however, due to the need for expensive 3D scanners, privacy issues with photographs or videos, and difficulty in making accurate tailoring measurements. We overcome these challenges by creating "The Virtual Caliper", which uses VR game controllers to make simple measurements. First, we establish what body measurements users can reliably make on their own body. We find several distance measurements to be good candidates and then verify that these are linearly related to 3D body shape as represented by the SMPL body model. The Virtual Caliper enables novice users to accurately measure themselves and create an avatar with their own body shape. We evaluate the metric accuracy relative to ground truth 3D body scan data, compare the method quantitatively to other avatar creation tools, and perform extensive perceptual studies. We also provide a software application to the community that enables novices to rapidly create avatars in fewer than five minutes. Not only is our approach more rapid than existing methods, it exports a metrically accurate 3D avatar model that is rigged and skinned.

Development of Female Torso Classification and Method of Patterns Shaping

Abstract Our study presents a new pattern-making approach that is composed of three major steps: to establish the new torso classification; to improve the pattern shaping method; to solve the problem of misfit of female dresses. New additional measurements were obtained from full bust, waist and hip circumferences and divided between front and back parts separately from 3D body scanning data. By creating 8 new torso subtypes Y1, Y2, A1, A2, B1, B2, C1, and C2, which reflect the body characteristics and torso morphology through distribution of bust girth between the front and the back, we have developed the Chinese female torso classification. On the basis of the new classification and the Japanese method of pattern block drafting, we improved the method of calculation of waist darts and the shaping of two kinds of female dresses: first kind doesn’t have the horizontal waist seam (one-piece dress) and second kind has the waist horizontal seam (two-pieces dress containing from the top and the skirt). The new torso subtypes and new pattern block shaping approach are taken into attention as the body characteristics will significantly improve the quality of clothes. New method of pattern pieces shaping in according with the characteristic features of a 3D virtual avatar allows to integrate this virtual pattern-generating approach into the pattern-making systems.

Longitudinal anthropometry of children and adolescents using 3D-body scanning.

3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children.

A 3D anthropometric sizing analysis system based on North American CAESAR 3D scan data for design of head wearable products

Abstract The present study developed a sizing analysis system for head-related product designs based on the Civilian American and European Surface Anthropometry Resource (CAESAR) database of North Americans. A total of 2299 heads in the CAESAR database were manually edited and 26 anthropometric landmarks were marked on the edited 3D heads to measure 30 anthropometric dimensions related to head-related product designs. The 3D anthropometric sizing analysis system (3D-ASAS) developed in the study provides analysis functions of a sizing system and representative face models by considering a target product, a target population, the number of size categories, and key anthropometric dimensions based on the CAESAR head measurements. Further research to reduce the efforts of manual editing and landmarking of 3D body scan data is discussed for efficient application of the 3D-ASAS to the design process of various wearable products.

Female breast shape categorization based on analysis of CAESAR 3D body scan data

In this study we explore the variation in female breast shape across the younger (age: 18–45), non-obese (BMI < 30) North American Caucasian population, a population that has not previously been well-represented in studies of breast shape. A method of classifying breast shape was developed based on multiple data-mining techniques. Forty-one relative measurements (i.e., ratios and angles) were constructed from 66 raw measurements (circumferences, depths, widths, etc.), extracted from 478 CAESAR (Civilian American and European Surface Anthropometry Resource) scans, using self-developed Matlab® programs. Seventy subjects were regarded as outliers and were removed. The remaining data were transformed and standardized to ensure robust analysis. To judge results, an algorithm was developed to visualize clustering outcomes in the form of side profiles of breasts. The results of three clustering methods, namely hierarchical, K-means, and K-medoids clustering, were compared. Finally, breast shapes were categorized into three and five groups by two different cluster number selection criteria proposed by the study: (1) based on misclassification rate; (2) based on the goodness-of-fit of the model. Several of the relative body measurements were identified to be critical in defining breast shape. The findings and the proposed methods of this study can contribute to the development of improved shape and sizing systems of bra products that work for both manufacturers and consumers. The new methodology developed in this study can also be applied to other types of intimate apparel products where an understanding of body shape plays a key role in body support, comfort, and fit.

3D 인체 스캔 데이터를 이용한 11~15세 성장기 여성의 유방형태에 따른 유형 분류

3D 인체 스캔 데이터를 이용한 11~15세 성장기 여성의 유방형태에 따른 유형 분류

슬랙스 형태 적합성 평가의 정량적 평가 기준 설정

This study presents quantitative evaluation standards for the shape fitness test, conducted in the process of the slacks fit test. This study aims to quantify appearance sensory test of slacks for the objectification of qualitative evaluation methods in existing shape fitness tests. The subjects were women of standard body type between the ages of 18 and 24. Slacks differing in their ease in waist girth, hip girth, crotch length and knee length were designed to test their shape fitness. The gap volume distribution between the body and slack, angle of the baseline by body part, and ratio of total thickness from the sideline using 3D human body scan data (which reflect the results of the appearance sensory test) were presented as quantitative evaluation standards. There were less wrinkles in the wrinkle/overstretch and ease categories of the appearance sensory test; in addition, ease was adequate and small enough to comfortably perform basic human activities in the standing upright posture. The gap volume distribution analysis between body and slacks showed that curves increased in the slacks surface along with an increase of ease in slacks and suggested that wrinkles also increased. In the baseline's horizontal categories in terms of a <TEX>$0^{\circ}$</TEX> horizontal angle, the range of angles were evaluated as adequate by the clothing expert group. The total thickness ratio of 0.5:0.5 divides into the sideline from the baseline.