Java3D技术在三维服装设计中的应用

随着服装工业的发展,三维服装CAD技术得到广泛的应用,通过三维人体测量建立人体三维数据模型,在虚拟的三维人体上进行交互式立体设计,最后完成二维平面服装衣片。大大提高了服装工业产品设计的水平和生产的效率。本文叙述了利用强大的Java3D技术进行三维显示和设计的基本原理和方法。     

适于网络试穿的快速三维服装仿真方法

三维服装仿真技术是虚拟试衣的核心,目前三维服装仿真常用有限元技术来实现,该方法仿真花费的时间较长不能满足网络试衣的要求。提出了一种基于服装裁剪分片技术的三维服装仿真方法,该方法参考服装设计知识将待仿真服装划分为若干衣片,然后用贝塞尔曲面分别模拟这些衣片,最后利用纹理映射技术把服装布料的图案映射到相应的衣片,得到服装三维仿真模型。实验表明利用该方法得到的三维服装模型能够把服装的基本试穿效果展示出来,而且所需的时间很短,可以满足在线试穿的要求。     

采用交互式缝合设置的三维服装模拟技术

目前, 国内外对于三维服装试衣技术的研究已逐渐深入, 但对于其中的关键步骤——服装衣片缝合信息的设置, 却少有成果. 服装的三维效果是通过缝合位于人体前后的二维衣片产生的, 精确及便捷的缝合设置是实现良好模拟效果的重要步骤之一. 在研究现有的三维虚拟试衣技术的基础上, 提出了缝合信息设定的方法流程, 并实现了交互式缝合设置过程. 在导入二维CAD衣片文件后, 经过交互式设置设定各衣片间的对应缝合边, 并以文件形式保存相关信息, 在试衣阶段通过导入该信息在对应衣片网格顶点间施加缝合力. 经实验, 通过该方法     

基于衣片网格局部变形的服装多样性研究

针对服装建模过程中,需要反复修改衣片来获得令人满意的虚拟服装模型以及计算复杂度高的问题,提出一种基于多控制点的衣片网格局部变形方法.该方法首先建立衣片网格模型,然后利用OpenGL的选择模式移动服装关键点,进而得到边界控制点,利用控制点对衣片网格模型进行局部变形,最后对衣片建立受力模型,通过虚拟缝合、碰撞检测以及纹理映射建立三维服装模型,展现服装整体效果,得到多样的服装模型.实验结果表明,由于在算法中不需要重新网络化,故具有较低的计算代价,同时也使得到的服装模型更加多样化.     

三维虚拟服装缝合技术研究

讨论三维计算机辅助服装设计系统中二维衣片转换为三维服装的有关技术问题。针对实现三维场景中服装的缝制及再现服装穿着的真实效果进行了深入研究。对于二维服装衣片的离散问题，提出基于正则栅格法思想的四边域网格剖分算法，界定了对位缝合和褶皱缝合的新概念，通过相应的边界调整方案解决了复杂服装的缝制问题；在缝合模拟过程中，分析衣片缝合前后缝合力的作用，并给出不同阶段的约束处理方法；最后针对服装同人模之间的碰撞，提出一个基于层次剖分法、融合包围盒检测技术特点有碰撞检测加速算法。这些技术均在三维虚拟服装缝制模拟系统中得以验证。     

基于二维衣片反求服装曲面方法研究

以服装立体裁剪所获得服装衣片结构线二维数据与人体模型特征线三维数据为基础,依据按已知条件构造可展面理论,研究在定长映射下服装衣片与服装曲面之间转换的几何学方法,进而实现服装曲面二维向三维的变换.     

基于人体部件模板组装的服装量身定制技术研究

通过采集人体样本数据,形成人体部件模板系列,根据客户提供的不同类型体形特征数据文件,提取出对应人体特征数据,生成个性化的三维虚拟人体模型,并最终生成个性化服装原型衣片.依照上述技术路线,设计了原型系统的架构,给出了功能结构,最后实现了原型系统.原型系统的运行结果表明,技术路线正确,系统方案合理,有助于推广电子化量身定制(eMTM)应用.     

基于角色几何碰撞体估计的实时服装仿真

提出了一种快速处理三维服装仿真中角色与服装碰撞的方法.该方法能够满足交互式实时仿真环境的需求.在预处理阶段,根据蒙皮动画的特点,将角色的几何形状以球和简化凸包等简单碰撞体进行估计.在实时模拟阶段,这些碰撞体跟随骨架运动并代替角色模型网格完成与虚拟服装之间的碰撞处理.此外,为了能够快速计算碰撞响应信息,该方法还利用外围映射机制进一步开发了相交测试的空间局部性.实验结果表明,应用该方法可以有效避免衣片与角色模型之间的相互穿透,同时大幅度地减少碰撞处理计算量.实时仿真系统对于复杂服装网格仍然保持了较高的模拟帧速率.     

3D服装CAD关键技术研究综述

随着3D设计技术的发展,3D GCAD也成为热点,但3D GCAD仍存在诸多难点。3D服装CAD系统是建立在3D人体模型上的尺寸信息提取、服装设计、虚拟试衣、动画模拟及基于互联网的定制、销售和展示等技术的集成。根据对其特征以及技术实现的总结,分析得出3D人体测量技术、3D服装人体建模技术、虚拟服装展示和3D服装展成2D衣片是3D服装CAD关键技术研究的热点,通过比较每种技术总结了3D服装CAD技术的发展趋势。     

着装间隙量空间形态分布研究及其应用综述

间隙量表征了人体服装之间的空间形态,是影响服装造型、舒适性和活动性的重要因素,三维服装CAD的发展促进了服装间隙量的研究.文中从测量分析、模拟分析和三维服装CAD应用三个方面综述了间隙量的理论研究与应用现状,并指出了当前间隙量领域的研究难点及其未来的发展方向.     

Generating unified model for dressed virtual humans

Scenes with crowds of dressed virtual humans are getting more attention and importance in 3D games and virtual reality applications. Crowd scenes, which include huge amounts of virtual humans, require complex computation for animation and rendering. In this research, new methods are proposed to generate efficient virtual human models by unifying a body and a garment into an animatable model, which has skinning parameters for the common skeleton-driven animation. The generated model has controlled complexity in geometry and semantic information. The unified model is constructed by using the correspondence between the body and the garment meshes. To establish the correspondence, two opposite optimization methods are proposed and compared: the first is to fit the body onto the garment and the second is to fit the garment onto the body. The innovative aspect of our method lies in supporting multiple correspondences between body and cloth parts. This enables us to handle the skirt model which is difficult to be processed by using previous works, due to its topological differences to the body model.     

Designing Personalized Garments with Body Movement

The standardized sizes used in the garment industry do not cover the range of individual differences in body shape for most people, leading to ill-fitting clothes, high return rates and overproduction. Recent research efforts in both industry and academia, therefore, focus on virtual try-on and on-demand fabrication of individually fitting garments. We propose an interactive design tool for creating custom-fit garments based on 3D body scans of the intended wearer. Our method explicitly incorporates transitions between various body poses to ensure a better fit and freedom of movement. The core of our method focuses on tools to create a 3D garment shape directly on an avatar without an underlying sewing pattern, and on the adjustment of that garment's rest shape while interpolating and moving through the different input poses. We alternate between cloth simulation and rest shape adjustment based on stretch to achieve the final shape of the garment. At any step in the real-time process, we allow for interactive changes to the garment. Once the garment shape is finalized for production, established techniques can be used to parameterize it into a 2D sewing pattern or transform it into a knitting pattern.     

基于款式设计的虚拟三维服装真实感效果模拟

介绍了由服装的二维款式设计研究三维款式真实感效果显示的步骤,并对人台参数化建模、服装的变空隙量模型等技术进行实践,提出了一种实现三维着装效果显示方法,为款式设计提供直观帮助.通过二维款式平面图到三维图形的映射得到可控的三维服装,通过精确可靠的三维数据模拟三维款式效果.在三维服装上添加全局纹理映射和多重纹理映射以及褶皱效果,增强服装设计可视化效果.     

A template of ease allowance for garments based on a 3D reverse methodology

Nowadays, with the very competitive environment and the emergence of the mass customization concept, garment design is become a crucial step for clothing companies. Indeed, garments should be designed quickly under controlled costs and perfectly fitted to consumers. No traditional pattern making in 2D matches these new constraints since it requires the production of expensive and time consuming physical prototypes. The study presented in this paper relies on 3D virtual design that lets achieve customized garments. An original image processing method based on ellipses and a reverse methodology using scans of a reference body and garment enables evaluation of the overall 3D ease of the garment. The garment is then designed virtually and the result is checked with a 3D simulation on the reference body.     

基于截面环的服装建模技术

在人体模型特征提取的基础上,采用水平切片的方法得到人体截面环,在将服装放松量转化为空隙度后,以空隙度为参数将人体截面环变形为服装截面环,根据角度同步前进法实现基于服装截面环的曲面构建.与已有方法相比,该方法建立在基于特征的参数化截面环之上,建模更加快捷,变形更容易控制.     

3D garment positioning using Hermite radial basis functions

Virtual Reality - Fitting an elegant 3D garment model onto a target 3D human model is crucial for garment design industry and virtual try-on systems. The alignment of the garment onto virtual...     

Detailed wrinkle generation of virtual garments from a single image

The presence of proper wrinkles is important while modeling realistic virtual garments. Unlike previously used full 3D information methods, our approach achieves detailed garment generation from a single image. First, we retrieve a garment image similar to the initial virtual garment based on content-based image retrieval (CBIR) method. Then, we preprocess the image with a combination of human body reshaping, image segmentation and shape recovery, to obtain the 3D wrinkle details. Finally, the garment height are synthesized into the virtual garment. For better suit the posture of the human body, excess garment energy are released to remove the unmatched wrinkles. We apply our method to various styles of virtual garments, and it enable virtual characters in general pose to be dressed in these garments and complete wrinkle generation. Compared with existing garment modeling methods, the experimental results show that the proposed method could quickly capture the realistic wrinkles of virtual garments with less manual operation and achieve more realistic wrinkles for virtual garments.

     

基于细分曲面的三维服装柔性实体模拟

提出一种基于细分曲面的三维服装柔性实体模拟算法,该算法将整个模拟过程分为两个阶段：首先利用四点细分曲面造型方法生成三维服装刚性曲面,然后在刚性曲面基础上通过引入织物的物理模型来模拟三维服装柔性曲面,通过物理和几何模拟方法有机结合,算法有效解决了复杂衣片间的缝合问题,较大地提高了模拟的计算效率,同时,也提出了一种基于细分曲面层次数据结构的碰撞检测算法,有效提高了模拟速度,提出的算法已全部在所开发的三维虚拟服装试衣系统中得以实现,实验结果表明：该算法具有模拟效率高、交互性强和易于计算机实现等优点。     

Fully Convolutional Graph Neural Networks for Parametric Virtual Try-On

We present a learning-based approach for virtual try-on applications based on a fully convolutional graph neural network. In contrast to existing data-driven models, which are trained for a specific garment or mesh topology, our fully convolutional model can cope with a large family of garments, represented as parametric predefined 2D panels with arbitrary mesh topology, including long dresses, shirts, and tight tops. Under the hood, our novel geometric deep learning approach learns to drape 3D garments by decoupling the three different sources of deformations that condition the fit of clothing: garment type, target body shape, and material. Specifically, we first learn a regressor that predicts the 3D drape of the input parametric garment when worn by a mean body shape. Then, after a mesh topology optimization step where we generate a sufficient level of detail for the input garment type, we further deform the mesh to reproduce deformations caused by the target body shape. Finally, we predict fine-scale details such as wrinkles that depend mostly on the garment material. We qualitatively and quantitatively demonstrate that our fully convolutional approach outperforms existing methods in terms of generalization capabilities and memory requirements, and therefore it opens the door to more general learning-based models for virtual try-on applications.