Customizing 3D garments based on volumetric deformation

Improving the reusability of design results is very important for garment design industry, since designing an elegant garment is usually labor-intensive and time-consuming. In this paper, we present a new approach for customizing 3D garment models. Our approach can transfer garment models initially dressed on a reference human model onto a target human model. To achieve this goal, firstly a spatial mapping between the two human models is established with the shape constraints of cross-sections. Secondly, the space around the clothed reference human model is tetrahedralized into five tetrahedral meshes each of which either can be worked dependently with its adjacent ones or can be worked independently. The clothed reference human model is parametrically encoded in the tetrahedral meshes. Thirdly, these tetrahedral meshes are deformed by fitting the reference human model onto the target human model by using constrained volumetric graph Laplacian deformation. The updated garment models are finally decoded from the deformed tetrahedral meshes. As a result, the updated garment models are fitted onto the target human model. Experiments show that our approach performs very well and has the potential to be used in the garment design industry.     

Automatic alignment for virtual fitting using 3D garment stretching and human body relocation

In recent years, researches on virtual fitting are mostly based on the data of garment pieces through Computer Aided Design. However, three-dimensional garment models are more intuitive, integrated and easy to access and manage. Therefore, we propose and design a method to automatically align virtual humans with three-dimensional garment models. Firstly, we basically align two models through three-dimensional geometric calculation and postural alteration of virtual humans. Then, we detect the penetration phenomena and define the points of the garment model penetrating into the human model as penetration points. Based on the penetration detection, we use Poisson mesh deformation to adjust the penetration points by imitating the adjustment process of dragging clothes. Finally, the results obtained from alignment can be directly used for physical-based simulation. Experimental results show that the method we propose can achieve good effects of alignment, and has good versatility and practicality.     

Physical simulation of wet clothing for virtual humans

We present a technique that simulates wet garments for virtual humans with realistic folds and wrinkles. Our approach combines three new models to allow realistic simulation of wet garments: (1) a simplified saturation model that modifies the masses, (2) a nonlinear friction model derived from previously reported, real-world measurements, and (3) a wrinkle model based on imperfection sensitivity theory. In contrast to previous approaches to wet cloth, the proposed models are supported by the experimental results reported in the textile literature with parameters varying over the course of the simulation. As a result, the wet garment motions simulated by our method are comparable to that of real wet garments. Our approach recognizes the special, practical importance of contact models with human skin and provides a specific skin-cloth friction solution. We evaluate our approach by draping a rotating sphere and simulating a typical garment on a virtual human in the rain. Both of these examples are typical scenarios within computer graphics research.     

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.

     

Virtual human modeling from photographs for garment industry

The research presented in this paper is to develop a technique of virtual human modeling for the garment industry from two photographs of a human body in two orthogonal views. Firstly, an efficient segmentation method is applied on the two photographs to obtain the contours of the human body. After this, a template-based feature extraction algorithm is introduced to determine the feature points on the human contours by human morphology rules. Finally, a view-dependent deformation technique is described to construct the virtual human body by using human contours. Our segmentation algorithm is derived from the Mumford-Shah segmentation technology and the level set formulation, and it is accelerated by applying multi-pyramid levels. The deformation technique is related to axial deformation. With our deformation method, the reference silhouettes (the front-view and right-view silhouettes of the template human model) and the target silhouettes (the front-view and right-view silhouettes of the human body from the photographs) are used to deform the template human model, which is represented by a polygonal mesh with predefined features. The self-intersection problem in the axial deformation is solved in our deformation approach. Compared with other virtual human modeling approaches, the speed of constructing the human model is increased; and our deformation technique has better continuity and local deformation properties. At the end of the paper, some potential applications for the garment industry are given to demonstrate the functionality of virtual human models constructed by our approach.     

Interactive virtual try-on clothing design systems

Clothing computer design systems include three integrated parts: garment pattern design in 2D/3D, virtual try-on and realistic clothing simulation. Some important results have been obtained in pattern design and clothing simulation since the 1980s. However, in the area of virtual try-on, only limited methods have been proposed which are applicable to some defined garment styles or under restrictive sewing assumptions. This paper presents a series of new techniques from virtually sewing up complex garment patterns on human models to visualizing design effects through physical-based real-time simulation. We first employ an hierarchy of ellipsoids to approximate human models in which the bounding ellipsoids are optimized recursively. We also present a new scheme for including contact friction and resolving collisions. Four types of user interactive operation are introduced to manipulate cloth patterns for pre-positioning, virtual sewing and later obtaining cloth simulation. In the cloth simulation, we propose a simplified cloth dynamic model and an integration scheme to realize a high quality real-time cloth simulation. We demonstrate the robustness of our proposed systems by complex garment style virtual try-on and cloth simulation.     

个性化三维虚拟试衣系统研究

为满足用户对虚拟试衣的个性化需求和提高虚拟试衣体验，提出一种包括自动化蒙皮、基于单张图片人脸三维自动重建、人体参数化变形以及服装模型穿透处理等模块的个性化虚拟试衣系统。设计了自动化蒙皮算法，解决已有虚拟试衣服装模型制作成本高的问题；通过基于单张图片的三维人脸自动重建和人体参数化变形，满足消费者个性化需求;运用基于自动透明贴图计算的服装穿透处理方法，改进系统试衣效果。实验表明，所提出的系统能够以较低的构建与运行成本实现较好的试衣效果，提供良好的个性化虚拟试衣体验。     

3D Face Modeling from Perspective-Views and Contour-Based Generic-Model

Three-dimensional human head modeling is useful in video-conferencing or other virtual reality applications. However, manual construction of 3D models using CAD tools is often expensive and time-consuming. Here we present a robust and efficient method for the construction of a 3D human head model from perspective images viewing from different angles. In our system, a generic head model is first used, then three images of the head are required to adjust the deformable contours on the generic model to make it closer to the target head. Our contributions are as follows. Our system uses perspective images that are more realistic than orthographic projection approximations used in earlier works. Also, for shaping and positioning face organs, we present a method for estimating the camera focal length and the 3D coordinates of facial landmarks when the camera transformation is known. We also provide an alternative for the 3D coordinates estimation using epipolar geometry when the extrinsic parameters are absent. Our experiments demonstrate that our approach produces good and realistic results.     

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.     

面向服装CAD的多因素驱动人体模型变形技术研究

在以人体模型为基础的3维服装CAD系统中,为了获得设计师所需形体尺寸各异的人体模型,提出了一种多因素驱动人体模型变形的方法.该方法将人体模型的变形驱动因素分为尺寸因素、姿态因素和局部体形因素3类,并相应地提出了尺寸驱动、姿态驱动及局部体形驱动的人体模型变形算法.其中尺寸驱动采用基于截面环的 算法和基于模板插值的算法,通过对人体特征尺寸进行改变来驱动人体变形;姿态驱动是通过关节变形算法来实现特定姿态的变形,并通过建立姿态库,以实现快速姿态匹配;局部体形驱动包括基于特征面尺寸和基于特征面形状的调整,以得到具有局部特征的人体.实例表明,该方法可对已有的人体进行快速变形,以获得用户所需的人体模型,从而满足了服装CAD中对人体模型的多样性需求.     

Context-aware garment modeling from sketches

Modeling of realistic garments is essential for creating believable virtual environments. Sketch-based modeling of garments presents an appealing, easy to use alternative to the established modeling approaches which are time consuming and require significant tailoring expertise. Unfortunately, the results created using existing sketch-based methods lack realism. Driven by human perception of garment sketches, we propose a context-aware garment sketch interpretation based on a set of observations about key factors that affect the shape of garments. Based on this analysis we develop a geometric method for sketch-based modeling of garments which obtains more realistic results than previous techniques. We demonstrate the effectiveness of our method on a variety of inputs and validate our approach via a user study where viewers were asked to compare the believability of our outputs versus previous ones.     

一种基于国标人体测量学数据的虚拟人建模方法

针对目前利用国标人体测量学数据构建的虚拟人模型,只有单一的骨骼层或皮肤层,不便于同时对虚拟人进行实时运动控制和皮肤动态变形研究的问题,提出一种利用GB 10000-88的19个人体测量学特征数据、用3ds max构造出虚拟人的皮肤网格、层级建模方法构建出虚拟人的骨骼关节运动模型与四元数球面混合插值技术相结合的虚拟人建模方法。实验结果表明,该方法构建的虚拟人双层模型有利于对准确的国标人体测量学数据的虚拟人角色进行建模、皮肤逼真变形、实时运动仿真和人机工效学分析。     

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.     

DeepGarment : 3D Garment Shape Estimation from a Single Image

3D garment capture is an important component for various applications such as free‐view point video, virtual avatars, online shopping, and virtual cloth fitting. Due to the complexity of the deformations, capturing 3D garment shapes requires controlled and specialized setups. A viable alternative is image‐based garment capture. Capturing 3D garment shapes from a single image, however, is a challenging problem and the current solutions come with assumptions on the lighting, camera calibration, complexity of human or mannequin poses considered, and more importantly a stable physical state for the garment and the underlying human body. In addition, most of the works require manual interaction and exhibit high run‐times. We propose a new technique that overcomes these limitations, making garment shape estimation from an image a practical approach for dynamic garment capture. Starting from synthetic garment shape data generated through physically based simulations from various human bodies in complex poses obtained through Mocap sequences, and rendered under varying camera positions and lighting conditions, our novel method learns a mapping from rendered garment images to the underlying 3D garment model. This is achieved by training Convolutional Neural Networks (CNN‐s) to estimate 3D vertex displacements from a template mesh with a specialized loss function. We illustrate that this technique is able to recover the global shape of dynamic 3D garments from a single image under varying factors such as challenging human poses, self occlusions, various camera poses and lighting conditions, at interactive rates. Improvement is shown if more than one view is integrated. Additionally, we show applications of our method to videos.     

面向不同体型特征的服装款式迁移方法

大部分成衣的设计以标准比例的人模作为参照,而对于非标准体型的顾客,标码 服装的大小尺寸则很难与之进行有效匹配。基于此,提出了一种面向不同体型特征的服装款 式迁移方法。首先,对于一批不同款式的服装,通过物理模拟的方式穿着到标模及非标模人 体之上,形成标模试穿的服装实例及非标模试穿的服装实例;其次,使用仿射变换表示同款 服装在标模及非标模下服装实例间的变形映射,并借助主成分分析法求解服装变形,在保留 因体型特征导致的服装形变的基础上,剔除由服装款式信息引起的服装形变;最后,将服装 变形用于标模到非标模的服装款式迁移,并使用平均离散曲率衡量迁移前后服装款式的改变 程度。实验结果表明,迁移后的服装携带了标模服装的款式信息,并保留了非标模服装的体 型特征。     

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     

Garment Modeling from a Single Image

Modeling of realistic garments is essential for online shopping and many other applications including virtual characters. Most of existing methods either require a multi‐camera capture setup or a restricted mannequin pose. We address the garment modeling problem according to a single input image. We design an all‐pose garment outline interpretation, and a shading‐based detail modeling algorithm. Our method first estimates the mannequin pose and body shape from the input image. It further interprets the garment outline with an oriented facet decided according to the mannequin pose to generate the initial 3D garment model. Shape details such as folds and wrinkles are modeled by shape‐from‐shading techniques, to improve the realism of the garment model. Our method achieves similar result quality as prior methods from just a single image, significantly improving the flexibility of garment modeling.     

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...     

A hybrid rendering algorithm for textile objects

Although realistic textile rendering has been widely used in virtual garment and try-on systems, a robust method to simulate textile with a realistic appearance and high fidelity is yet to be established. We propose to use a novel hybrid geometric- and image-based rendering (GIBR) method to achieve photo realistic representation of textile products. The image-based technique, with its radiance synthesis algorithm, enables us to recover the reflectance properties of textile in an environment photo, and thus can render the appearance of textile material. The geometry-based technique, with its traditional illumination model of assigning illumination parameters extracted from the original scene (such as radiance and chroma dispatch), makes it possible to interactively manipulate 3D virtual objects in the “real” environment. Our realistic textile rendering method has advantages over the traditional ones in its easiness to implement and its wide range of applications.     

Feature based 3D garment design through 2D sketches

This paper presents a new approach for intuitively modeling a three-dimensional (3D) garment around a 3D human model by two-dimensional (2D) sketches input. Our approach is feature based—every human model has pre-defined features, and the constructed garments are related to the features on human models. Firstly, a feature template for creating a customized 3D garment is defined according to the features on a human model; secondly, the profiles of the 3D garment are specified through 2D sketches; finally, a smooth mesh surface interpolating the specified profiles is constructed by a modified variational subdivision scheme. The resulting mesh surface can be cut and flattened into 2D patterns to be manufactured. Our approach provides a 3D design tool to create garment patterns directly in the 3D space through 2D strokes, which is a characteristic not available in other computer aided garment design systems. The constructed garment patterns are related to the features on a human model, so the patterns can be regenerated automatically when creating the same style of garment for other human models. Our technique can greatly improve the efficiency and the quality of pattern making in the garment industry.