Parametric body shape model of standing children aged 3–11 years

A statistical body shape model (SBSM) for children was developed for generating a child body shape with desired anthropometric parameters. A standardised template mesh was fit to whole-body laser scan data from 137 children aged 3–11 years. The mesh coordinates along with a set of surface landmarks and 27 manually measured anthropometric variables were analysed using principal component (PC) analysis. PC scores were associated with anthropometric predictors such as stature, body mass index (BMI) and ratio of erect sitting height to stature (SHS) using a regression model. When the original scan data were compared with the predictions of the SBSM using each subject's stature, BMI and SHS, the mean absolute error was 10.4 ± 5.8 mm, and 95th percentile error was 24.0 ± 18.5 mm. The model, publicly available online, will have utility for a wide range of applications.

Practitioner Summary: A statistical body shape model for children helps to account for inter-individual variability in body shapes as well as anthropometric dimensions. This parametric modelling approach is useful for reliable prediction of the body shape of a specific child with a few given predictors such as stature, body mass index and age.     

Body shape analyses of large persons in South Korea

Despite the prevalence of obesity and overweight, anthropometric characteristics of large individuals have not been extensively studied. This study investigated body shapes of large persons (Broca index ≥ 20, BMI ≥ 25 or WHR>1.0) using stature-normalised body dimensions data from the latest South Korean anthropometric survey. For each sex, a factor analysis was performed on the anthropometric data set to identify the key factors that explain the shape variability; and then, a cluster analysis was conducted on the factor scores data to determine a set of representative body types. The body types were labelled in terms of their distinct shape characteristics and their relative frequencies were computed for each of the four age groups considered: the 10s, 20s–30s, 40s–50s and 60s. The study findings may facilitate creating artefacts that anthropometrically accommodate large individuals, developing digital human models of large persons and designing future ergonomics studies on largeness.

Practitioner Summary: This study investigated body shapes of large persons using anthropometric data from South Korea. For each sex, multivariate statistical analyses were conducted to identify the key factors of the body shape variability and determine the representative body types. The study findings may facilitate designing artefacts that anthropometrically accommodate large persons.     

Research on lower body shape of late pregnant women in Shanghai area of China

Anthropometric data, especially the data of lower body of late-pregnant women, has become an immediate need for ergonomic design of maternity products, such as clothing, related motherhood supplies, maternity support products, and so on. So 55 late pregnant women in Shanghai area of China were randomly selected for this lower body shape research. By anthropometric measurement method 18 dimensions were measured to characterize lower body shape of late pregnant women. Mean values, standard deviations (SD), coefficients of variation, and percentiles for each variable were estimated. It was found that the morphology of hip and abdomen mostly influenced the lower body shape. Then according to the characters of hip and abdomen, the late pregnant women's lower body shapes were divided into two types. Moreover this paper also analyzed the change trend of lower body shape along late pregnancy months (7 to 9th months). As a result of this research, the late pregnant women's lower body shapes were described from different aspects which were thought to provide a guide for the maternity products design.Relevance to industryThe anthropometric data is essential to design reasonable and professional maternity products for late pregnant women, such as maternity support products, maternity clothing and so on. Especially this study can benefit the maternity garment industry. Moreover utilization of the anthropometric data, product designers would be able to outfit to a wider range of target users.     

Estimating spine shape in lateral sleep positions using silhouette-derived body shape models

This study aims at evaluating spinal alignment during sleep by combining personalized human models with mattress indentation measurements. A generic surface model has been developed that can be personalized based on anthropometric parameters derived from silhouette extraction. Shape assessment of the personalized surface models, performed by comparison with 3-D surface scans of the trunk, showed a mean unsigned distance of 9.77 mm between modeled and scanned surface meshes. The surface model is combined with an inner skeleton model, allowing the model to simulate distinct sleep postures. An automatic fitting algorithm sets the appropriate degrees of freedom to position the model on the measured indentation according to the adopted sleep posture. Validation on lateral sleep positions showed good intraclass correlations (0.73–0.88) between estimated and measured angular spinal deformations, indicating that silhouette-derived body shape models provide a valuable tool for the unobtrusive assessment of spinal alignment during sleep.Relevance to industry: A common drawback of the available techniques to assess spinal deformation on bedding systems is that they interfere with the actual sleep process. The current study presents a novel method based on silhouette-derived body shape models in order to estimate spine shape during sleep unobtrusively.     

双目立体视觉在动车车身关键尺寸检测中的应用

针对动车（CRH）车身尺寸范围大、检测项目复杂、车型变化多,不容易实现在线测量的难题,首先提出了大型动车车身关键尺寸的测量方案,利用双目电荷耦合装置（CCD）立体视觉建立各个关键尺寸的视觉测量子站,同时利用激光跟踪仪及相关坐标变换算法,完成对各个CCD相机测量子站的全局标定;各个测量子站利用立体空间球检测技术,对局部关键尺寸进行测量;同时构建了基于小波分析的神经网络温度误差补偿模型,使空间距离补偿后的精度能达到0.05 mm。将该方法与三坐标测量机测得的数据对比验证,可以发现该方法操作简单、灵活性高、精度较高,可有效解决动车车身关键尺寸检测问题。     

Parametric 3D modeling of young women's lower bodies based on shape classification

Three-dimensional (3D) human body modeling is an important research direction in the field of clothing virtual design. On the basis of 3D human body scanning, this paper studied a method to build a 3D parametric lower body model according to body classification. The research includes three main parts. (1) Anthropometry and body shape classification. We randomly selected 333 young women ages 18–25 years old in Northeast China as the experimental sample. Then we divided the lower body shape into three categories using principal component analysis and K-means clustering. (2) Determination of feature cross sections and points, and reconstruction of feature curves. According to the average values of each body type, we obtained the mean reference body by Euclidean distance method. We determined feature cross sections and points, and extracted the 3D coordinates of the feature points of the mean reference body to reconstruct the feature curves. (3) The surface lofting and establishment of parametric 3D lower body model. According to the shape characteristics of the lower body, we constructed the guiding lines for the crotch and lower limbs, and established parametric lower body models for three body types.Relevance to industry3D human modeling is an important part of garment industry digitization. This research provides an effective way to construct a parametric 3D lower body model. The method offers a reference for the parametric virtual human modeling and virtual fitting of trousers.     

An approach to estimate body dimensions through constant body ratio benchmarks

Building a new anthropometric database is a difficult and costly job that requires considerable manpower and time. However, most designers and engineers do not know how to convert old anthropometric data into applicable new data with minimal errors and costs (Wang et al., 1999). To simplify the process of converting old anthropometric data into useful new data, this study analyzed the available data in paired body dimensions in an attempt to determine constant body ratio (CBR) benchmarks that are independent of gender and age. In total, 483 CBR benchmarks were identified and verified from 35,245 ratios analyzed. Additionally, 197 estimation formulae, taking as inputs 19 easily measured body dimensions, were built using 483 CBR benchmarks. Based on the results for 30 recruited participants, this study determined that the described approach is more accurate and cost-effective than alternative techniques.     

Classification of upper lateral body shapes for the apparel industry

The lateral body shape is a critical determiner of the fit of garments. Either visual assessment or statistical analysis methods have been used to classify the lateral body types. These methods are limited to some extent since various anthropometric features inherently coexist and interact in a human body shape. This study aims to develop objective criteria for the classification of upper lateral body shapes integrating visual assessment and statistical analysis. The three‐dimensional scan data of 246 women between 18 and 49 years old were visually classified into four lateral body shapes by an expert panel. In addition, the back space and lateral angles extracted from the scan data were employed for further statistical analyses. Multinomial logistic regressions were used to develop logit models for lateral body types. It was concluded that the resulting logit models could classify lateral body types and calculate the probability of a set of body scan data being classified as a certain lateral body type. It is expected that this probability might be a guideline to quantify the characteristics of the lateral body shape in the apparel industry. © 2010 Wiley Periodicals, Inc.     

Fuzzy classification of young women's lower body based on anthropometric measurement

The traditional method of body classification is discrete, using crisp and rather dichotomous classification methods; there are many shortcomings for ergonomic design of clothing products by this method. This paper proposes a fuzzy method to classify lower body shapes based on triangular fuzzy numbers. By using factor analysis and correlation analysis, we found that the height, the waist girth, and the difference of hip-waist are crucial dimensions to represent lower body shape. We then classified the lower body shape into three categories according to the difference of hip-to-waist, and finally used the membership of triangular fuzzy numbers to represent the lower body shapes. Results show that the fuzzy method of body classification can more accurately represents body information than the traditional method without increasing the number of body types. Additionally, we established that the mean of the height, waist girth and hip girth of the young women of northeast China increased by about 0.8 cm, 1.5 cm and 1.4 cm respectively compared with ten years ago.Relevance to industry: Anthropometric data is the basis of garment pattern design, and body classification is a necessary precondition for developing a garment size system. These research achievements will add value to the pattern design of young women's lower body clothing, the development of new sizing systems and related industries.     

Three-dimensional human shape inference from silhouettes: reconstruction and validation

Silhouettes are robust image features that provide considerable evidence about the three-dimensional (3D) shape of a human body. The information they provide is, however, incomplete and prior knowledge has to be integrated to reconstruction algorithms in order to obtain realistic body models. This paper presents a method that integrates both geometric and statistical priors to reconstruct the shape of a subject assuming a standardized posture from a frontal and a lateral silhouette. The method is comprised of three successive steps. First, a non-linear function that connects the silhouette appearances and the body shapes is learnt and used to create a first approximation. Then, the body shape is deformed globally along the principal directions of the population (obtained by performing principal component analysis over 359 subjects) to follow the contours of the silhouettes. Finally, the body shape is deformed locally to ensure it fits the input silhouettes as well as possible. Experimental results showed a mean absolute 3D error of 8 mm with ideal silhouettes extraction. Furthermore, experiments on body measurements (circumferences or distances between two points on the body) resulted in a mean error of 11 mm.     

Estimating body shape of dressed humans

The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans.     

Foot shape modeling

This study is an attempt to show how a "standard" foot can be parameterized using foot length, foot width, foot height, and a measure of foot curvature so that foot shape can be predicted using these simple anthropometric measures. The prediction model was generated using 40 Hong Kong Chinese men, and the model was validated using a different group of 25 Hong Kong Chinese men. The results show that each individual foot shape may be predicted to a mean accuracy of 2.1 mm for the left foot and 2.4 mm for the right foot. Application of this research includes the potential design and development of custom footwear without the necessity of expensive 3-D scanning of feet.     

Object representation and recognition in shape spaces

In this paper, we describe a shape space based approach for invariant object representation and recognition. In this approach, an object and all its similarity transformed versions are identified with a single point in a high-dimensional manifold called the shape space. Object recognition is achieved by measuring the geodesic distance between an observed object and a model in the shape space. This approach produced promising results in 2D object recognition experiments: it is invariant to similarity transformations and is relatively insensitive to noise and occlusion. Potentially, it can also be used for 3D object recognition.     

Anthropometry of male agricultural workers of western India for the design of tools and equipments

Agricultural workers and farmers in India perform most of the agricultural operations manually. Hence, for the design of farm equipments, hand tools and machinery involving human efforts, region specific anthropometric data is needed. A survey was conducted to collect anthropometric dimensions of male agricultural workers in the state of Maharashtra in India in the age group of 18–60 years. Almost 59 body dimensions were selected for the measurement from the recommendations by All India Coordinated Research Project (AICRP) on Human Engineering and Safety in Agriculture (HESA) and requisite by digital human manikin modeling. Total 303 male agricultural workers were selected from 23 districts of Maharashtra by convenience sampling. Repeatability of the measurements was checked by paired samples t test. From the measured dimensions, the values of minimum, maximum, mean, standard deviation (SD), standard error of mean (SEM), coefficient of variation (CV), 5th and 95th percentile values were determined. The results of the survey were compared with results of other regions of India and other countries.Relevance to industryThe anthropometric data of user population is very utile for the design/improvement of farm equipments/implements for agricultural workers in order to reduce drudgery, increase efficiency, safety and comfort.     

个性化三维人体模型快速建模方法

采用模型重用的思想,通过输入21个人体测量学参数对标准人体模型进行编辑,实时获得相应体型的个性化三维人体模型．该方法使得编辑过程能够实时完成;生成的人体模型可以方便地驱动;精选的21个人体测量学参数覆盖了人体各处的细节,能够比较完整地描述人体的外形特征,满足对人体模型个性化的需求．     

Comparison of measured and self-reported anthropometric information among firefighters: implications and applications

This study evaluated the accuracy of self-reported body weight and height compared to measured values among firefighters and identified factors associated with reporting error. A total of 863 male and 88 female firefighters in four US regions participated in the study. The results showed that both men and women underestimated their body weight ( ? 0.4 ± 4.1, ? 1.1 ± 3.6 kg) and overestimated their height (29 ± 18 , 17 ± 16 mm). Women underestimated more than men on weight (p = 0.022) and men overestimated more than women on height (p < 0.001). Reporting errors on weight were increased with overweight status (p < 0.001) and were disproportionate among subgroups. About 27% men and 24% women had reporting errors on weight greater than ± 2.2 kg, and 59% men and 28% women had reporting errors on height greater than 25 mm.

Practitioner Summary: This study along with literature revealed that the self-reported approach is not a sustainable option for anthropometric surveys, even for gathering data from physically active professional groups, such as firefighters, who presumably are knowledgeable of their body dimensions. Self-reported anthropometric information is undependable in important population subgroups.     

形状的全尺度可视化表示与识别

目的 视觉目标的形状特征表示和识别是图像领域中的重要问题。在实际应用中,视角、形变、遮挡和噪声等干扰因素造成识别精度较低,且大数据场景需要算法具有较高的学习效率。针对这些问题,本文提出一种全尺度可视化形状表示方法。方法 在尺度空间的所有尺度上对形状轮廓提取形状的不变量特征,获得形状的全尺度特征。将获得的全部特征紧凑地表示为单幅彩色图像,得到形状特征的可视化表示。将表示形状特征的彩色图像输入双路卷积网络模型,完成形状分类和检索任务。结果 通过对原始形状加入旋转、遮挡和噪声等不同干扰的定性实验,验证了本文方法具有旋转和缩放不变性,以及对铰接变换、遮挡和噪声等干扰的鲁棒性。在通用数据集上进行形状分类和形状检索的定量实验,所得准确率在不同数据集上均超过对比算法。在MPEG-7数据集上精度达到99.57%,对比算法的最好结果为98.84%。在铰接和射影变换数据集上皆达到100%的识别精度,而对比算法的最好结果分别为89.75%和95%。结论 本文提出的全尺度可视化形状表示方法,通过一幅彩色图像紧凑地表达了全部形状信息。通过卷积模型既学习了轮廓点间的形状特征关系,又学习了不同尺度间的形状特征关系。本文方法在视角变化、局部遮挡、铰接变形和噪声等干扰下能保持较高的识别正确率,可应用于图像采集干扰较多以及红外或深度图像的目标识别,并适用于大数据场景下的识别任务。     

An approach to estimate body dimensions through constant body ratio benchmarks

Building a new anthropometric database is a difficult and costly job that requires considerable manpower and time. However, most designers and engineers do not know how to convert old anthropometric data into applicable new data with minimal errors and costs (Wang et al., 1999). To simplify the process of converting old anthropometric data into useful new data, this study analyzed the available data in paired body dimensions in an attempt to determine constant body ratio (CBR) benchmarks that are independent of gender and age. In total, 483 CBR benchmarks were identified and verified from 35,245 ratios analyzed. Additionally, 197 estimation formulae, taking as inputs 19 easily measured body dimensions, were built using 483 CBR benchmarks. Based on the results for 30 recruited participants, this study determined that the described approach is more accurate and cost-effective than alternative techniques.     

基于国家标准的三维扫描人体尺寸提取技术

针对人体点云模型特征点和尺寸自动提取的难点问题,提出基于国家标准统计数据的人体关键尺寸提取技术。采用国家标准GB10000 1988《中国成年人人体尺寸》所提供的基础数据划分特征点的搜索域,首先,在搜索域内将坐标值和点到直线投影距离比较相结合来提取人体特征点;然后通过改进的凸壳法计算特征平面轮廓周长进行围度尺寸测量,再利用z坐标差值和两点的距离实现长度尺寸计算。实验表明,该方法受人体体型的影响小,尺寸测量鲁棒性好、计算速度快、精度高。