一种基于人体测量学的三维人体快速建模方法研究与实现

常用的个性化三维人体建模方法存在数据量大,处理过程复杂,不适合Web应用的不足,该文提出一种新的快速进行三维人体建模的方法,该方法根据人体测量学和人体解剖学原理,结合人体表面特征点和特征线分布规律,应用超椭圆仿真人体各截面、采用层次参数驱动设计思想,实现快速创建个性化三维人体模型。该方法具有满足实时要求、交互参数少,易于控制,误差小、模型真实感强等优点,并可以准确地提供骨骼关节点和人体特征点．适于三维仿真形象动态设计、人体运动模拟和虚拟服装试衣等多种应用。     

基于国标人体测量学数据的虚拟人缩放方法

具有准确人体测量学数据的虚拟人模型在虚拟制造和虚拟维修领域有重要的理论和现实意义。此外,根据某些人体测量学数据,参照典型的人体模型生成特定的虚拟人,即实现人体模型的参数化控制,对于合理地进行人机功效分析也有重要的应用价值。该文在分析我国成年人体测量学数据标准的基础上,通过研究Jack软件中人体模型表示方法和人体测量学数据之间的映射关系,提出了一种基于人体测量学数据的人体模型动态缩放方法。利用该方法在Jack软件中建立了基于国标人体测量学数据的人体模型动态缩放子系统。     

一种基于人体测量学的三维人体快速建模方法研究与实现

常用的个性化三维人体建模方法存在数据量大,处理过程复杂,不适合Web应用的不足,该文提出一种新的快速进行三维人体建模的方法,该方法根据人体测量学和人体解剖学原理,结合人体表面特征点和特征线分布规律,应用超椭圆仿真人体各截面、采用层次参数驱动设计思想,实现快速创建个性化三维人体模型。该方法具有满足实时要求、交互参数少,易于控制,误差小、模型真实感强等优点,并可以准确地提供骨骼关节点和人体特征点,适于三维仿真形象动态设计、人体运动模拟和虚拟服装试衣等多种应用。     

基于尺寸建立个性化人体模型的方法

近年来,人体模型定制已成为计算机图形学领域的重要研究课题之一。文中提出一种基于少量人体尺寸生成个性化人体模型的方法——分块优化法。首先,根据MPI人体扫描模型数据库获得人体外形形变参数与尺寸参数,采用线性相关分析方法实现由若干尺寸恢复完整人体尺寸集。其次,通过参数优化的线性回归方法分析各部位三维人体外形参数与二维尺寸数据之间的关系,并根据输入尺寸对人体模型进行进一步精调。实验表明,上述方法能够生成准确反映人体外形的人体模型。     

面向服装设计的人体建模及人体参数化*

利用人体曲面重构法构建人体参数化模型,并对人体参数化模型进行参数化变形。人体曲面重建分为预处理和曲面生成两个步骤。预处理包括坐标调整、特征识别,然后利用人体切片技术和曲面光顺技术得到人体曲面和人体参数化模型。对参数化人体模型施加尺寸变形和插值变形两种参数化变形手段,得到个性化人体和系列化人体,从而为服装设计提供很好的模型支撑。     

三维人体的草绘建模方法

提出了一种三维人体的草绘建模方法,允许用户分层次绘制人体骨架线和轮廓线草图,并快速生成三维人体模型.该方法的特征主要表现在两个方面:首先,采用层次化的人体截面模板进行形变,并使用基于距离的描述子在人体模板库中检索最符合用户绘制的模板,使结果模型更能体现人体草图特性;其次,采用参数驱动的三维人体模型生成方法,将草图轮廓特征与模板轮廓进行对应并计算三维形变参数,最后对人体模板进行形变生成三维人体模型.实验结果表明,该方法能够快速构建符合用户绘制意图的三维人体模型.     

面向服装个性化定制的多视角轮廓三维人体快速重建方法

服装个性化在线定制需要围绕用户形状参数进行设计,传统的量体方法获取的用户形状参数误差高、反馈慢,亟需构建一种三维人体重建方法能够快速感知用户人体形状.针对此问题,提出了一种面向服装个性化定制的多视角轮廓三维人体快速重建方法.利用多级空洞卷积分割网络(multilevel dilated convolution semantic network,MDS-Net)提取人体轮廓图像中整体和局部特征,实现轮廓图像的语义分割;利用躯干参数提取网络(torso parameter extraction network,TPE-Net)提取多视角人体轮廓分割图的形状和姿势参数;利用主成分分析(principal component analysis,PCA)提取三维人体模型潜层空间的语义特征,并映射为由TPE-Net输出的形状和姿势参数,从而实现三维人体重建.在PyTorch环境下,采用4个数据集进行实验验证,结果表明,MDS-Net在测试集上的分割mIoU评分平均为0.881,能够实现整体分割和局部细节保留;TPE-Net在测试集上形状参数预测准确率为0.74,关节预测偏移距离与运动树中的索引呈正...     

基于Kinect的人体实时三维重建及其应用

目前,人体三维重建技术在建模前一般需要采集从多个视角观察人体的数据,并限定人体的姿势,不能很好地用于需要人体模型的交互式应用中.针对这个问题,提出一种基于单个Kinect的渐进式人体重建方法.首先结合特征点检测算法和校错处理,对深度视频帧中人体上的特征点进行定位;其次对身体尺寸进行测算或估算,并在对视频流的处理中渐进式地补充与完善;最后根据以上信息对人体进行分块参数化建模和合成,得到人体模型.实验结果表明,在尺寸不完整的情况下,该方法即可重建包含肢体结构语义的完整人体,易于实现局部模型或姿势的修改,并在虚拟试衣应用中体现出良好的实时性和交互性.     

由正交图像造型三维个性化虚拟人体模型

基于正、侧、背面4幅正交人体图像,变形模板人体模型后得到带服饰纹理的个性化虚拟人．以截面环为基本几何元素,给出了模板人体模型的生成和变形方法,建立了截面环和三维人体骨架之间的内在关联;自动提取图像上的人体特征点,生成二维图像上的人体骨架;由三维人体骨架和二维图像上人体骨架之间的对应关系,建立截面环和人体图像之间的对应关系;从人体图像上获取截面环的形状参数,通过参数化变形截面环得到个性化的虚拟人体模型．与已有方法相比,该方法建立在基于特征的参数化框架之上,变形更容易控制,消除了三维模型和二维图像之间对应的不确定性,避免了人体变形中的自交现象,效率高、真实感效果较好．     

面向工业设计的人体模型参数化研究

以人体测量学理论、人体尺寸国家标准、中国人解剖学数值为依据，建立了人体尺寸数据库，开发了以C Builder为编程环境的、面向工业设计用的参数化人体模型生成系统．分析了STL文件格式，编制了该系统与UG，3DSMAX等三维造型软件的接口程序．最后，利用该系统生成的人体模型来检测由UG制作的赛车驾驶室与人体尺寸是否协调．     

一种具有逼真效果的虚拟人动画生成方法

针对传统的虚拟人动画逼真度低、动画生成复杂、且动画存在飘移现象的问题,提出了一种基于视频关键帧获取运动数据的虚拟人动画生成方法。首先利用线性混合蒙皮算法建立了新的人体几何模型;其次利用正向运动学方法驱动虚拟人的骨骼模型,并利用平移补偿原则消除虚拟人运动中的飘移现象;最终实现了基于双目正交视觉获取关节运动参数的虚拟人动画。实验结果表明,新方法能逼真地模拟真实人体动作,且方法易于实现、实用性强。     

Anthropometric body modeling based on orthogonal-view images

This paper presents an efficient and convenient method for creating an anthropometric model of a real person. First, 3D surface body models based on orthogonal-view photographs are reconstructed, and then skeletal systems for the reconstructed models are matched. A total of 26 anthropometric data items are measured using the surface and skeletal models. Some anthropometric data are measured directly on the deformed surface models, whereas others are estimated from the matched skeletal systems by kinematic analysis. A comparison of the anthropometric data from the reconstructed model with data from the corresponding real person demonstrates that the methodology proposed in this paper has high efficiency and precision. These models will satisfy consumer demand for higher product personalization and therefore product comfort, and they are likely to be widely used in future ergonomic research.Relevance to industryA convenient and efficient method to create individual anthropometric models is proposed. These models will help people create their own anthropometry databases and satisfy their demand for higher product personalization and therefore product comfort. The industrial applications include mass customization, computer-aided drafting, online custom-made design, and ergonomic evaluation.     

Child body shape measurement using depth cameras and a statistical body shape model

We present a new method for rapidly measuring child body shapes from noisy, incomplete data captured from low-cost depth cameras. This method fits the data using a statistical body shape model (SBSM) to find a complete avatar in the realistic body shape space. The method also predicts a set of standard anthropometric data for a specific subject without measuring dimensions directly from the fitted model. Since the SBSM was developed using principal component (PC) analysis, we formulate an optimisation problem to fit the model in which the degrees of freedom are defined in PC-score space. The mean unsigned distance between the fitted-model based on depth-camera data and the high-resolution laser scan data was 9.4 mm with a standard deviation (SD) of 5.1 mm. For the torso, the mean distance was 2.9 mm (SD 1.4 mm). The correlations between standard anthropometric dimensions predicted by the SBSM and manually measured dimensions exceeded 0.9.     

Motion planning for humanoid robots based on virtual constraints extracted from recorded human movements

In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. In this paper, we consider motion planning for humanoid robots based on the concept of virtual holonomic constraints. At first, recorded kinematic data of particular human motions are analyzed in order to extract consistent geometric relations among various joint angles defining the instantaneous postures. Second, a simplified human body representation leads to dynamics of an underactuated mechanical system with parameters based on anthropometric data. Motion planning for humanoid robots of similar structure can be carried out by considering solutions of reduced dynamics obtained by imposing the virtual holonomic constraints that are found in human movements. The relevance of such a reduced mathematical model in accordance with the real human motions under study is shown. Since the virtual constraints must be imposed on the robot dynamics by feedback control, the design procedure for a suitable controller is briefly discussed.     

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.     

Interactive motion mapping for real‐time character control

It is now possible to capture the 3D motion of the human body on consumer hardware and to puppet in real time skeleton‐based virtual characters. However, many characters do not have humanoid skeletons. Characters such as spiders and caterpillars do not have boned skeletons at all, and these characters have very different shapes and motions. In general, character control under arbitrary shape and motion transformations is unsolved ‐ how might these motions be mapped? We control characters with a method which avoids the rigging‐skinning pipeline — source and target characters do not have skeletons or rigs. We use interactively‐defined sparse pose correspondences to learn a mapping between arbitrary 3D point source sequences and mesh target sequences. Then, we puppet the target character in real time. We demonstrate the versatility of our method through results on diverse virtual characters with different input motion controllers. Our method provides a fast, flexible, and intuitive interface for arbitrary motion mapping which provides new ways to control characters for real‐time animation.     

基于LAN的计算机视觉与虚拟现实集成模型研究

进入80年代后期,虚拟现实技术取得了迅速的发展,目前作为一个全新的技术生长点受到了国内外学者的广泛关注。文中提出了一个基于LAN计算机视觉与虚拟现实集成模型。论述了系统实现及实验结果。研究结果表明,把计算机视觉技术与虚拟现实技术“集成”在一起,从现实世界精炼出关键参数供虚拟现实技术所用,可构成简便灵活的虚拟现实系统,文中在研究大空间跟踪中采用了该模型,证明了该模型的可行性及优点。     

Experimental study of a momentum-based method for identifying the inertia barycentric parameters of a human body

Physical modeling, simulation and analysis of an individual human body require inertia properties of the body segments of the human. Such subject-specific inertia data can be obtained only by measuring the individual human body as opposed to be derived from statistically generated anthropometric database. This paper presents experimental validation of a momentum-based approach for identifying the barycentric parameters of an individual human body which fully describes the inertia properties of the human. The identification algorithm is derived from the impulse–momentum equations of the human body which is assumed to be a multibody system with tree-type topology. Since the impulse–momentum equations are linear in terms of the unknown barycentric parameters, these parameters can be solved from the equations using a least-squares method. The approach does not require measuring or estimating accelerations and joint forces/torques because they do not appear in the impulse–momentum equations, and thus, the resulting identification procedure is less demanding on measurement data than the methods derived from the equations of motion. In this paper the test results of the identification method are validated by comparing the identified inertia parameters against the statistically established anthropometric data. Additionally, the identification results are also confirmed by comparing the contact forces using inverse dynamics to those obtained by forces plates.     

A hyper elasticity method for interactive virtual design of hearing aids

We present a computational efficient method for isotropic hyper elasticity based on functional analysis. By selecting a class of shape functions, we arrive at a computational scheme which yields very sparse tensors. This enables fast computations of the hyper elastic energy potential and its derivatives. We achieve efficiency and performance through the use of shape functions that are linear in their parameters and through rotation into the eigenspace of the right Cauchy–Green strain tensor. This makes near real time evaluation of hyper elasticity of complex meshes on CPU relatively easy to implement. The approach does not rely on a specific shape function or material model but offers a general framework for isotropic hyper elasticity. The method is aimed at interactive and accurate non-linear hyper elastic modeling for a wide range of industrial virtual design applications, which we exemplify by insertion of hearing aid domes into the ear canal. We validate the method for tetrahedral meshes with linear shape functions with an Ogden material model by comparing simulations to deformations of real material. We illustrate the use of other shape functions and models using uniform cubic B-splines in combination with Riemannian elasticity.