Real-time simulation and visualisation of cloth using edge-based adaptive meshes

Real-time rendering and the animation of realistic virtual environments and characters has progressed at a great pace, following advances in computer graphics hardware in the last decade. The role of cloth simulation is becoming ever more important in the quest to improve the realism of virtual environments. The real-time simulation of cloth and clothing is important for many applications such as virtual reality, crowd simulation, games and software for online clothes shopping. A large number of polygons are necessary to depict the highly exible nature of cloth with wrinkling and frequent changes in its curvature. In combination with the physical calculations which model the deformations, the effort required to simulate cloth in detail is very computationally expensive resulting in much diffculty for its realistic simulation at interactive frame rates. Real-time cloth simulations can lack quality and realism compared to their offline counterparts, since coarse meshes must often be employed for performance reasons. The focus of this thesis is to develop techniques to allow the real-time simulation of realistic cloth and clothing. Adaptive meshes have previously been developed to act as a bridge between low and high polygon meshes, aiming to adaptively exploit variations in the shape of the cloth. The mesh complexity is dynamically increased or refined to balance quality against computational cost during a simulation. A limitation of many approaches is they do not often consider the decimation or coarsening of previously refined areas, or otherwise are not fast enough for real-time applications. A novel edge-based adaptive mesh is developed for the fast incremental refinement and coarsening of a triangular mesh. A mass-spring network is integrated into the mesh permitting the real-time adaptive simulation of cloth, and techniques are developed for the simulation of clothing on an animated character

Diffusion Shape Prior for Wrinkle-Accurate Cloth Registration

Registering clothes from 4D scans with vertex-accurate correspondence is challenging, yet important for dynamic appearance modeling and physics parameter estimation from real-world data. However, previous methods either rely on texture information, which is not always reliable, or achieve only coarse-level alignment. In this work, we present a novel approach to enabling accurate surface registration of texture-less clothes with large deformation. Our key idea is to effectively leverage a shape prior learned from pre-captured clothing using diffusion models. We also propose a multi-stage guidance scheme based on learned functional maps, which stabilizes registration for large-scale deformation even when they vary significantly from training data. Using high-fidelity real captured clothes, our experiments show that the proposed approach based on diffusion models generalizes better than surface registration with VAE or PCA-based priors, outperforming both optimization-based and learning-based non-rigid registration methods for both interpolation and extrapolation tests.Comment: Project page: https://www-users.cse.umn.edu/~guo00109/projects/3dv2024

Men’s Jeans Fit Based on Body Shape Categorization

The purpose of this study was to categorize lower body shape in men and to investigate the interplay between body shape and fitting issues appearing in men’s jeans. More specifically, the goal of the study was to improve apparel fit based on body shape. The detailed objectives of the study were to: (1) Categorize male body shapes using statistical analysis; (2) use 3D virtual fitting technology to assess fit and develop a shape-driven pants block pattern for each body shape. This quantitative study was conducted in three stages: (1) categorizing the body shape of 1420 male scans, aged 18-35, from the SizeUSA dataset, (2) develop a shape-driven pants block pattern for each identified body shape, and (3) validate the developed blocks by virtually trying the shape-driven block pattern on fit testers from different body shape groups. Exploratory Factor Analysis (EFA) and cluster analysis were used for body shape categorization, which resulted in three different body shapes: (1) Flat-Straight, (2) Moderate Curvy-Straight, and (3) Curvy. Three fit models were selected from each identified body shape group and then patterns were developed using Armstrong’s (2005) jeans foundation method. Patterns were modified and fitted to the selected representative fit models of each body shape group. The developed shape-driven block patterns were simulated on the fit testers to further explore the relationship between body shape and fit issues. This study suggests that two individuals with identical body measurements may experience very different fit problems tailored to their different body shapes. It was found that each body shape would exclusively experience unique fit issues. Furthermore, the shape driven block patterns were found to be highly correlated with their host body shape category. This research implies that if the mass customization process starts with block patterns that are engineered for specific body shape categories significantly less fit issues would appear and the desired fit would be achieved in fewer fitting sessions

Automatic tailoring and cloth modelling for animation characters.

The construction of realistic characters has become increasingly important to the production of blockbuster films, TV series and computer games. The outfit of character plays an important role in the application of virtual characters. It is one of the key elements reflects the personality of character. Virtual clothing refers to the process that constructs outfits for virtual characters, and currently, it is widely used in mainly two areas, fashion industry and computer animation. In fashion industry, virtual clothing technology is an effective tool which creates, edits and pre-visualises cloth design patterns efficiently. However, using this method requires lots of tailoring expertises. In computer animation, geometric modelling methods are widely used for cloth modelling due to their simplicity and intuitiveness. However, because of the shortage of tailoring knowledge among animation artists, current existing cloth design patterns can not be used directly by animation artists, and the appearance of cloth depends heavily on the skill of artists. Moreover, geometric modelling methods requires lots of manual operations. This tediousness is worsen by modelling same style cloth for different characters with different body shapes and proportions. This thesis addresses this problem and presents a new virtual clothing method which includes automatic character measuring, automatic cloth pattern adjustment, and cloth patterns assembling. There are two main contributions in this research. Firstly, a geodesic curvature flow based geodesic computation scheme is presented for acquiring length measurements from character. Due to the fast growing demand on usage of high resolution character model in animation production, the increasing number of characters need to be handled simultaneously as well as improving the reusability of 3D model in film production, the efficiency of modelling cloth for multiple high resolution character is very important. In order to improve the efficiency of measuring character for cloth fitting, a fast geodesic algorithm that has linear time complexity with a small bounded error is also presented. Secondly, a cloth pattern adjusting genetic algorithm is developed for automatic cloth fitting and retargeting. For the reason that that body shapes and proportions vary largely in character design, fitting and transferring cloth to a different character is a challenging task. This thesis considers the cloth fitting process as an optimization procedure. It optimizes both the shape and size of each cloth pattern automatically, the integrity, design and size of each cloth pattern are evaluated in order to create 3D cloth for any character with different body shapes and proportions while preserve the original cloth design. By automating the cloth modelling process, it empowers the creativity of animation artists and improves their productivity by allowing them to use a large amount of existing cloth design patterns in fashion industry to create various clothes and to transfer same design cloth to characters with different body shapes and proportions with ease

Design For Movement: Block Pattern Design For Stretch Performancewear

This thesis is in 2 volumesPattern drafting techniques for woven block patterns have been well established. Applying existing techniques with modifications to generate patterns for modern stretch fabrics can be successful but it is often at a cost. In the development of a stretch pattern, an acceptable fit cannot be guaranteed merely by using a rationalised simple pattern profile shape. Producing a pattern, without darts, to closely adhere to the contours of the body without restricting movement, is a contradiction in design terms. In woven fabric, darts and ease are used to manipulate the fabric around the form and allow movement. However, in stretch knit fabric the development of a block pattern involves the synthesis of information from a variety of disciplines and requires a more specialist approach. This study has endeavoured to show that a new interpretation of pattern design principles is needed to create an improved stretch block pattern for stretch knit performancewear. This work has been refined based on a new method of classifying stretch fabric parameters and personal observation of the effect of stretch distortion characteristics and the changes that occur in the twodimensional pattern profile, when stretched to conform to the threedimensional body. The results of this study will provide a more SCientific and practical approach to assessing stretch fabric parameters as an integral part of block pattern design for stretch performancewear. The fabric stretch potential has been maximised to contour the body for optimum fit, providing comfort and mobility without the need for redistribution of the fabric when activity ceases. A method of creating a stretch block pattern from direct measurements to replicate the body shape and proportions was devised which can be reduplicated. This study addresses primarily the designer/pattern cutter who has a passion for good fit, which enhances comfort and mobility, who does not necessarily have a scientific background. However this study is relevant to the textile technologist concerned with proposing a standard to compare stretch fabrics for garment production. It should also appeal to the computer programmer concerned with the link between 3D body scanning and interpreting the body profile accurately in the 2D pattern draft

Recognition and Manipulation of Deformable Objects Using Predictive Thin Shell Modeling

This thesis focuses on the task of dexterous manipulation of deformable objects, and in particular, clothing and garments. The task of manipulating deformable objects such as clothing can be broken down into a series of sub-tasks: (1) perceive and pick up garment, and then identify garment and recognize its pose; (2) using a manipulation strategy, regrasp the object to put it into a canonical state; (3) scan the surface of the object to find wrinkles, and use an iron to remove the wrinkles; (4) starting from the wrinkle-free state, fold the garment according to pre-planned sequence of manipulations with optimized trajectories; In this thesis, we will address all the phases of this process. A key contribution of the work is innovative use of simulation. We use offline simulation results to predict states of deformable objects (i.e. cloth, fabric, clothing) that are then recognized by a robotic vision/grasping system to correctly pick up and manipulate these objects. The recognition will use the simulation engine to deform the models in real time to find correct matches. The simulation will also be used to find the optimized trajectories for the manipulation of the garments, such as the garment folding

RECREATING AND SIMULATING DIGITAL COSTUMES FROM A STAGE PRODUCTION OF \u3ci\u3eMEDEA\u3c/i\u3e

This thesis investigates a technique to effectively construct and simulate costumes from a stage production Medea, in a dynamic cloth simulation application like Maya\u27s nDynamics. This was done by using data collected from real-world fabric tests and costume construction in the theatre\u27s costume studio. Fabric tests were conducted and recorded, by testing costume fabrics for drape and behavior with two collision objects. These tests were recreated digitally in Maya to derive appropriate parameters for the digital fabric, by comparing with the original reference. Basic mannequin models were created using the actors\u27 measurements and skeleton-rigged to enable animation. The costumes were then modeled and constrained according to the construction process observed in the costume studio to achieve the same style and stitch as the real costumes. Scenes selected and recorded from Medea were used as reference to animate the actors\u27 models. The costumes were assigned the parameters derived from the fabric tests to produce the simulations. Finally, the scenes were lit and rendered out to obtain the final videos which were compared to the original recordings to ascertain the accuracy of simulation. By obtaining and refining simulation parameters from simple fabric collision tests, and modeling the digital costumes following the procedures derived from real-life costume construction, realistic costume simulation was achieved