The apparel industry has witnessed a significant shift toward 3D virtual design, driven by advances in simulation and digitization technologies. Central to this transformation are digital twins, which allow designers to test and refine garment designs virtually, reducing reliance on physical prototyping. A critical aspect of this process is accurately capturing the drape behavior of fabrics, as it impacts both the aesthetic and functional properties of garments. Traditional fabric digitization methods involve mechanical testing of fabric samples, but they are labor-intensive, costly, and require specialized equipment. Recently, AI-based digitization techniques have emerged, offering potential advantages in terms of cost and logistics, though their accuracy remains uncertain. This study addresses the gap in knowledge regarding the accuracy of AI-based fabric digitization by utilizing the Cusick drape test-a standardized method for assessing fabric drape behavior. We introduce a reference digitization pipeline based on traditional mechanical testing and perform a comprehensive comparative study of six commercially available digitization methods, including both traditional and AI-based approaches. Using a diverse set of fabrics, we evaluate the accuracy of the digitized fabrics against real-world measurements. Our results demonstrate that AI-based methods can achieve competitive accuracy, while also highlighting areas for further improvement. We present a publicly available dataset containing real fabric properties, their digitized versions, as well as their corresponding real and digital drape metrics, which can serve as a valuable resource for further research and development in fabric digitization.

Digital garments are set to revolutionize the apparel industry in the way we design, produce, market, sell and try-on real garments. But for digital garments to play a central role, from designer to consumer, they must be a faithful digital replica of their real counterpart: a digital twin. Yet, most industry-grade tools used in the apparel industry do not focus on accuracy, but rather on producing fast and plausible drapes for interactive editing and quick feedback, thus limiting the value and the potential of digital garments. The key to accuracy lies in using the proper underlying simulation technology, well documented in the academic literature but historically sidelined in the apparel industry in favor of simulation speed. In this paper, we describe our industry-grade cloth simulation engine, built with a strong focus on accuracy rather than sheer speed. Using a global integration scheme and adopting state of the art simulation practices from the Computer Graphics field, we evaluate a wide range of algorithms to improve its convergence and overall performance. We provide qualitative and quantitative insights on the cost and capabilities of each of these features, with the aim of giving valuable feedback and useful guidelines to practitioners seeking to implement an accurate and robust draping simulator.

Abstract Estimating fabric mechanical properties is crucial to create realistic digital twins. Existing methods typically require testing physical fabric samples with expensive devices or cumbersome capture setups. In this work, we propose a method to estimate fabric mechanics just from known manufacturer metadata such as the fabric family, the density, the composition, and the thickness. Further, to alleviate the need to know the fabric family –which might be ambiguous or unknown for nonspecialists–we propose an end‐to‐end neural method that works with planar images of the textile as input. We evaluate our methods using extensive tests that include the industry standard Cusick and demonstrate that both of them produce drapes that strongly correlate with the ground truth estimates provided by lab equipment. Our method is the first to propose such a simple capture method for mechanical properties outperforming other methods that require testing the fabric in specific setups.

Seams play a fundamental role in the way a garment looks, fits, feels and behaves. Seams can have very different shapes and mechanical properties depending on how fabric is overlapped, folded and stitched together, with garment designers often choosing specific seam and stitch type combinations depending on the appearance and behavior they want for the garment. Yet, virtually all 3D CAD tools for fashion and visual effects ignore most of the visual and mechanical complexity of seams, and just treat them as joint edges, their simplest possible form, drastically limiting the fidelity of digital garments. In this paper, we present a method that models seams following their true, real-life construction. Each seam brings together and overlaps the fabric pieces to be sewn, folds the fabric according to the type of seam, and stitches the resulting assembly following the type of stitch. To avoid dealing with the complexities of folding in 3D space, we cast the problem into a sequence of simpler 2D problems where we can easily shape the seam and produce a result free of self-intersections, before lifting the folded geometry back to 3D space. We run a series of constrained optimizations to enforce spatial properties in these 2D settings, allowing us to treat asymmetric seams, gatherings and overlapping construction orders. Using a variety of common seams and stitches, we show how our approach substantially improves the visual appearance of full garments, for a better and more predictive digital replica.

Abstract This paper presents a method to combine triangle and yarn models in cloth simulation, and hence leverage their best features. The majority of a garment uses a triangle‐based model, which reduces the overall computational and memory cost. Key areas of the garment use a yarn‐based model, which elicits rich effects such as structural nonlinearity and plasticity. To combine both models in a seamless and robust manner, we solve two major technical challenges. We propose an enriched kinematic representation that augments triangle‐based deformations with yarn‐level details. Naïve enrichment suffers from kinematic redundancy, but we devise an optimal kinematic filter that allows a smooth transition between triangle and yarn models. We also introduce a preconditioner that resolves the poor conditioning produced by the extremely different inertia of triangle and yarn nodes. This preconditioner deals effectively with rank deficiency introduced by the kinematic filter. We demonstrate that mixed yarns and triangles succeed to efficiently capture rich effects in garment fit and drape.

Abstract To deploy yarn‐level cloth simulations in production environments, it is paramount to design very efficient implementations, which mitigate the cost of the extremely high resolution. To this end, nodal discretizations aligned with the regularity of the fabric structure provide an optimal setting for efficient GPU implementations. However, nodal discretizations complicate the design of robust and controllable bending. In this paper, we address this challenge, and propose a model of bending that is both robust and controllable, and employs only nodal degrees of freedom. We extract information of yarn and fabric orientation implicitly from the nodal degrees of freedom, with no need to augment the model explicitly. But most importantly, and unlike previous formulations that use implicit orientations, the computation of bending forces bears no overhead with respect to other nodal forces such as stretch. This is possible by tracking optimal orientations efficiently. We demonstrate the impact of our bending model in examples with controllable anisotropy, as well as ironing, wrinkling, and plasticity.

Thin shells --- solids that are thin in one dimension compared to the other two --- often emit rich nonlinear sounds when struck. Strong excitations can even cause chaotic thin-shell vibrations, producing sounds whose energy spectrum diffuses from low to high frequencies over time --- a phenomenon known as wave turbulence. It is all these nonlinearities that grant shells such as cymbals and gongs their characteristic "glinting" sound. Yet, simulation models that efficiently capture these sound effects remain elusive. We propose a physically based, multi-scale reduced simulation method to synthesize nonlinear thin-shell sounds. We first split nonlinear vibrations into two scales, with a small low-frequency part simulated in a fully nonlinear way, and a high-frequency part containing many more modes approximated through time-varying linearization. This allows us to capture interesting nonlinearities in the shells' deformation, tens of times faster than previous approaches. Furthermore, we propose a method that enriches simulated sounds with wave turbulent sound details through a phenomenological diffusion model in the frequency domain, and thereby sidestep the expensive simulation of chaotic high-frequency dynamics. We show several examples of our simulations, illustrating the efficiency and realism of our model.

Abstract Most popular methods in cloth rendering rely on volumetric data in order to model complex optical phenomena such as sub‐surface scattering. These approaches are able to produce very realistic illumination results, but their volumetric representations are costly to compute and render, forfeiting any interactive feedback. In this paper, we introduce a method based on the Graphics Processing Unit (GPU) for voxelization and visualization, suitable for both interactive and offline rendering. Recent features in the OpenGL model, like the ability to dynamically address arbitrary buffers and allocate bindless textures, are combined into our pipeline to interactively voxelize millions of polygons into a set of large three‐dimensional (3D) textures (>109 elements), generating a volume with sub‐voxel accuracy, which is suitable even for high‐density woven cloth such as linen.

Cloth is made of yarns that are stitched together forming semi-regular patterns. Due to the complexity of stitches and patterns, the macroscopic behavior of cloth is dictated by the contact interactions between yarns, not by the mechanical properties of yarns alone. The computation of cloth mechanics at the yarn level appears as a computationally complex and costly process at first sight, due to the need to resolve many fine-scale contact interactions. We propose instead an efficient representation of cloth at the yarn level that treats yarn-yarn contacts as persistent, but with the possibility to slide, thereby avoiding expensive contact handling altogether. We introduce a compact representation of yarn geometry and kinematics, capturing the essential deformation modes of yarn crossings, loops, stitches, and stacks, with a minimum cost. Based on this representation, we design force models that reproduce the characteristic macroscopic behavior of yarn-based fabrics. Our approach is suited for both woven and knitted fabrics. We demonstrate the efficiency of our method on simulations with millions of degrees of freedom (hundreds of thousands of yarn loops), almost one order of magnitude faster than previous techniques. We also compare the different macroscopic behavior under woven and knitted patterns with the same yarn density.

Crumpling a thin sheet produces a characteristic sound, comprised of distinct clicking sounds corresponding to buckling events. We propose a physically based algorithm that automatically synthesizes crumpling sounds for a given thin shell animation. The resulting sound is a superposition of individually synthesized clicking sounds corresponding to visually significant and insignificant buckling events. We identify visually significant buckling events on the dynamically evolving thin surface mesh, and instantiate visually insignificant buckling events via a stochastic model that seeks to mimic the power-law distribution of buckling energies observed in many materials. In either case, the synthesis of a buckling sound employs linear modal analysis of the deformed thin shell. Because different buckling events in general occur at different deformed configurations, the question arises whether the calculation of linear modes can be reused. We amortize the cost of the linear modal analysis by dynamically partitioning the mesh into nearly rigid pieces: the modal analysis of a rigidly moving piece is retained over time, and the modal analysis of the assembly is obtained via Component Mode Synthesis (CMS). We illustrate our approach through a series of examples and a perceptual user study, demonstrating the utility of the sound synthesis method in producing realistic sounds at practical computation times.

This paper introduces a tactile rendering algorithm for wearable cutaneous devices that stimulate the skin through local contact surface modulation. The first step in the algorithm simulates contact between a skin model and virtual objects, and computes the contact surface to be rendered. The accuracy of this surface is maximized by simulating soft skin with its characteristic nonlinear behavior. The second step takes the desired contact surface as input, and computes the device configuration by solving an optimization problem, i.e., minimizing the deviation between the contact surface in the virtual environment and the contact surface rendered by the device. The method is implemented on a thimble-like wearable device.

The large-scale mechanical behavior of woven cloth is determined by the mechanical properties of the yarns, the weave pattern, and frictional contact between yarns. Using standard simulation methods for elastic rod models and yarn-yarn contact handling, the simulation of woven garments at realistic yarn densities is deemed intractable. This paper introduces an efficient solution for simulating woven cloth at the yarn level. Central to our solution is a novel discretization of interlaced yarns based on yarn crossings and yarn sliding, which allows modeling yarn-yarn contact implicitly, avoiding contact handling at yarn crossings altogether. Combined with models for internal yarn forces and inter-yarn frictional contact, as well as a massively parallel solver, we are able to simulate garments with hundreds of thousands of yarn crossings at practical frame-rates on a desktop machine, showing combinations of large-scale and fine-scale effects induced by yarn-level mechanics.

Haptic interaction with different types of materials in the same scene is a challenging task, mainly due to the specific coupling mechanisms that are usually required for either fluid, deformable or rigid media. Dynamically-changing materials, such as melting or freezing objects, present additional challenges by adding another layer of complexity in the interaction between the scene and the haptic proxy. In this paper, we address these issues through a common simulation framework, based on Smoothed-Particle Hydrodynamics, and enable haptic interaction simultaneously with fluid, elastic and rigid bodies, as well as their melting or freezing. We introduce a mechanism to deal with state changes, allowing the perception of haptic feedback during the process, and a set of dynamic mechanisms to enrich the interaction through the proxy. We decouple the haptic and visual loops through a dual GPU implementation. An initial evaluation of the approach is performed through performance and feedback measurements, as well as a small user study assessing the capability of users to recognize the different states of matter they interact with.

The command of haptic devices for rendering direct interaction with the hand requires thorough knowledge of the forces and deformations caused by contact interactions on the fingers. In this paper, we propose an algorithm to simulate nonlinear elasticity under frictional contact, with the goal of establishing a model-based strategy to command haptic devices and to render direct hand interaction. The key novelty in our algorithm is an approach to model the extremely nonlinear elasticity of finger skin and flesh using strain-limiting constraints, which are seamlessly combined with frictional contact constraints in a standard constrained dynamics solver. We show that our approach enables haptic rendering of rich and compelling deformations of the fingertip.

Virtual walking, a fundamental task in Virtual Reality (VR), is greatly influenced by the locomotion interface being used, by the specificities of input and output devices, and by the way the virtual environment is represented. No matter how virtual walking is controlled, the generation of realistic virtual trajectories is absolutely required for some applications, especially those dedicated to the study of walking behaviors in VR, navigation through virtual places for architecture, rehabilitation and training. Previous studies focused on evaluating the realism of locomotion trajectories have mostly considered the result of the locomotion task (efficiency, accuracy) and its subjective perception (presence, cybersickness). Few focused on the locomotion trajectory itself, but in situation of geometrically constrained task. In this paper, we study the realism of unconstrained trajectories produced during virtual walking by addressing the following question: did the user reach his destination by virtually walking along a trajectory he would have followed in similar real conditions? To this end, we propose a comprehensive evaluation framework consisting on a set of trajectographical criteria and a locomotion model to generate reference trajectories. We consider a simple locomotion task where users walk between two oriented points in space. The travel path is analyzed both geometrically and temporally in comparison to simulated reference trajectories. In addition, we demonstrate the framework over a user study which considered an initial set of common and frequent virtual walking conditions, namely different input devices, output display devices, control laws, and visualization modalities. The study provides insight into the relative contributions of each condition to the overall realism of the resulting virtual trajectories.

Immersive spaces such as 4-sided displays with stereo viewing and high-quality tracking provide a very engaging and realistic virtual experience. However, walking is inherently limited by the restricted physical space, both due to the screens (limited translation) and the missing back screen (limited rotation). In this paper, we propose three novel locomotion techniques that have three concurrent goals: keep the user safe from reaching the translational and rotational boundaries; increase the amount of real walking and finally, provide a more enjoyable and ecological interaction paradigm compared to traditional controller-based approaches. We notably introduce the "Virtual Companion", which uses a small bird to guide the user through VEs larger than the physical space. We evaluate the three new techniques through a user study with travel-to-target and path following tasks. The study provides insight into the relative strengths of each new technique for the three aforementioned goals. Specifically, if speed and accuracy are paramount, traditional controller interfaces augmented with our novel warning techniques may be more appropriate; if physical walking is more important, two of our paradigms (extended Magic Barrier Tape and Constrained Wand) should be preferred; last, fun and ecological criteria would favor the Virtual Companion.

Haptic interaction with virtual objects is a major concern in the virtual reality field. There are many physically-based efficient models that enable the simulation of a specific type of media, e.g. fluid volumes, deformable and rigid bodies. However, combining these often heterogeneous algorithms in the same virtual world in order to simulate and interact with different types of media can be a complex task. In this paper, we propose the first haptic rendering technique for the simulation and the interaction with multistate media, namely fluids, deformable bodies and rigid bodies, in real-time and with 6DoF haptic feedback. Based on the Smoothed-Particle Hydrodynamics (SPH) physical model for all three types of media, our method avoids the complexity of dealing with different algorithms and their coupling. We achieve high update rates while simulating a physically-based virtual world governed by fluid and elasticity theories, and show how to render interaction forces and torques through a 6DoF haptic device.

We often interact with fluids in our daily life, either through tools such as when holding a glass of water or directly with our body when we swim or we wash our hands. Multimodal interactions with virtual fluids would greatly improve the simulations realism, particularly through haptic interaction. However, achieving realistic, stable, and real-time force feedback from fluids is particularly challenging. In this work, we propose a novel approach that allows real-time six Degrees of Freedom (DoF) haptic interaction with fluids of variable viscosity. Our haptic rendering technique, based on a Smoothed-Particle Hydrodynamics physical model, provides a realistic haptic feedback through physically based forces. 6DoF haptic interaction with fluids is made possible thanks to a new coupling scheme and a unified particle model, allowing the use of arbitrary-shaped rigid bodies. Particularly, fluid containers can be created to hold fluid and hence transmit to the user force feedback coming from fluid stirring, pouring, shaking, and scooping, to name a few. Moreover, we adapted an existing visual rendering algorithm to meet the frame rate requirements of the haptic algorithms. We evaluate and illustrate the main features of our approach through different scenarios, highlighting the 6DoF haptic feedback and the use of containers.

In most virtual reality simulations the virtual world is larger than the real walking workspace. The workspace is often bounded by the tracking area or the display devices. This paper describes a novel interaction metaphor called the Magic Barrier Tape, which allows a user to navigate in a potentially infinite virtual scene while confined to a restricted walking workspace. The technique relies on the barrier tape metaphor and its do not cross implicit message by surrounding the walking workspace with a virtual barrier tape in the scene. Therefore, the technique informs the user about the boundaries of his walking workspace, providing an environment safe from collisions and tracking problems. It uses a hybrid position/rate control mechanism to enable real walking inside the workspace and rate control navigation to move beyond the boundaries by pushing on the virtual barrier tape. It provides an easy, intuitive and safe way of navigating in a virtual scene, without break of immersion. Two experiments were conducted in order to evaluate the Magic Barrier Tape by comparing it to two state-of-the-art navigation techniques. Results showed that the Magic Barrier Tape was faster and more appreciated than the compared techniques, while being more natural and less tiring. Considering it can be used in many different virtual reality systems, it is an interaction metaphor suitable for many different applications, from the entertainment field to training simulations scenarios.