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17121 research outputs found
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Dynamic Cutting Simulation Using Elastic Snapping for Mesh Quality Optimization
No full textIn this manuscript, we present a novel cutting method that involves using a vertex-snapping strategy to fit the boundary surface onto the cutting path while avoiding generating new elements. We employ a point cloud with polynomial fitting to generate the cutting path, allowing for operation with unscheduled cuts and potential perturbations. Efficient geometry operations are developed to handle topological changes during progressive cutting. While it is challenging to optimize the mesh quality and accurately align the cut surface with the cutting path, we propose an innovative strategy that converts this geometric problem into a quasi-static elastic problem. This involves solving a constrained elastic problem within an auxiliary simulation, where the system optimizes the mesh quality when reaching equilibrium. Furthermore, we propose modifications to a GPU-based matrix-free solver, enabling efficient updates of the precomputed data stored in the GPU memory and thus ensuring real-time performance.Computer Graphics ForumOriginal Article44
Differentiable Search Based Halftoning
No full textHalftoning is fundamental to image reproduction on devices with a limited set of output levels, such as printers. Halftoning algorithms reproduce continuous-tone images by distributing dots with a fixed tone but variable size or spacing. Search-based approaches optimize for a dot distribution that minimizes a given visual loss function w.r.t. an input image. This class of methods is not only the most intuitive and versatile but can also yield the highest quality results depending on the merit of the employed loss function. However, their combinatorial nature makes them computationally inefficient. We introduce the first differentiable search-based halftoning algorithm. Our proposed method can be natively used to perform multi-color, multi-level halftoning. Our main insight lies in introducing a relaxation in the discrete choice of dot assignment during the backward pass of the optimization. We achieve this by associating a fictitious distance from the image plane to each dot, embedding the problem in three dimensions. We also introduce a novel loss component that operates in the frequency domain and provides a better visual loss when combined with existing image similarity metrics. We validate our approach by demonstrating that it outperforms stochastic optimization methods in both speed and objective value, while also scaling significantly better to large images. The code is available at https:gitlab.mpi-klsb.mpg.de/aidam-public/differentiable-halftoningComputer Graphics ForumStylization and Image Processing44
Single-Shot Facial Appearance Acquisition without Statistical Appearance Priors
No full textSingle-shot in-the-wild facial reflectance acquisition has been a long-standing challenge in the field of computer graphics and computer vision. Current state-of-the-art methods are typically learning-based methods, pre-trained on a dataset of facial reflectance data. However, due to the high cost and time-consuming nature of gathering these datasets, they are usually limited in the number of subjects covered and hence are prone to biases in the dataset. To this end, we propose a novel multi-stage guided optimization with differentiable rendering to tackle this problem, without the use of statistical facial appearance priors. This makes our method immune to these biases, and we demonstrate the advantage with qualitative and quantitative evaluations against current state-of-the-art methods.Eurographics 2025 - Short PapersShort Paper
The IMPULSE Project: Advancing Immersive Digitization for Sustainable Digital Cultural Heritage Integration within ECCCH.
No full textThis article critically analyses the assumptions of the European Collaborative Cloud for Cultural Heritage (ECCCH) and explores how the impact and results of the ongoing IMPULSE project can contribute to and integrate within its broader framework. In particular, IMPULSE offers a relevant testing ground for ECCCH to advance the management of immersive digital cultural heritage objects. A key focus is on the sustainability of IMPULSE's outcomes and their potential to address the fragmentation that characterizes the digital cultural heritage landscape. This fragmentation affects different aspects of the digitization process, such as technical issues, standardization, interoperability, user experience, and legal dimensions. Many cultural collections in Europe are still not digitized, with significantly low figures for high-quality three-dimensional representations essential for scientific collaboration. Existing standards and methodologies are neither uniform, traceable, nor fully secure, and practical techniques enabling accurate physical simulations of digitized heritage objects remain largely unexplored. Against this issue, IMPULSE is positioned to develop and test new approaches connected to metadata standardisation and immersive interaction with digital objects that capture not only the visual but also the dynamic characteristics of cultural heritage assets and practices. Starting from the analysis of these aspects and in view of the alignment with the strategic objectives of the European Commission, IMPULSE's ongoing research contributes to technical de-fragmentation by providing the development of an EU-based Multi-User Virtual Environment (MUVE) for visualising and interacting with 3D assets. Its approach emphasizes interoperability, ensuring that data formats, protocols, and tools align with existing cultural heritage infrastructures, making integration into platforms and digital twins more feasible. IMPULSE research is also aimed at defining protocols and tools to provide data in a standardised and easily understandable format, based on three IMPULSE prototypes. The ongoing research on IMPULSE is relevant when considering uninvolved users, as it provides prototypes and tests of immersive interaction geared towards diverse audiences (academics, artists, cultural and creative industries). By focusing on immersive interaction with CH objects in virtual environments, IMPULSE contributes not only to advancing digital heritage methodologies but also to ensuring their sustainability and integration within the ECCCH.Digital HeritageCollaborative Cloud for CH (ECHOES SESSION
ChromBrain Wall: A Virtual Reality Game Featuring Customized Full-Body Movement for Long-Term Physical and Cognitive Training in Older Adults
No full textAging brings challenges to the daily lives of older adults due to the decline in physical and cognitive functions. Although virtual reality (VR) exercise games can promote the physical and cognitive health of older adults, existing games are not suitable for personalized continuous training for the elderly due to unreasonable cognitive activation patterns, exercise task designs, and difficulty settings. To address this, we developed ChromaBrain Wall, a VR cognitive training exercise game with customized full-body movements, for the long-term exercise and cognitive inhibition training of healthy older adults. We then conducted an 8-month longitudinal user study on 40 older adults aged 65 and above, and the results showed that after the training, the older adults' exercise performance and cognitive inhibition abilities were significantly enhanced, and these benefits lasted for 6 months. Moreover, qualitative feedback indicated that the older adults had a positive attitude towards long-term use of ChromaBrain Wall, which increased their training motivation and compliance. This shows that ChromaBrain Wall has both short-term and long-term effects in enhancing the exercise performance and cognitive inhibition of older adults, providing a new approach for the health intervention of the elderly.Pacific Graphics Conference Papers, Posters, and DemosInteraction & Virtual Realit
Automatic Reconstruction of Woven Cloth from a Single Close-up Image
No full textDigital replication of woven fabrics presents significant challenges across a variety of sectors, from online retail to entertainment industries. To address this, we introduce an inverse rendering pipeline designed to estimate pattern, geometry, and appearance parameters of woven fabrics given a single close-up image as input. Our work is capable of simultaneously optimizing both discrete and continuous parameters without manual interventions. It outputs a wide array of parameters, encompassing discrete elements like weave patterns, ply and fiber number, using Simulated Annealing. It also recovers continuous parameters such as reflection and transmission components, aligning them with the target appearance through differentiable rendering. For irregularities caused by deformation and flyaways, we use 2D Gaussians to approximate them as a post-processing step. Our work does not pursue perfect matching of all fine details, it targets an automatic and end-to-end reconstruction pipeline that is robust to slight camera rotations and room light conditions within an acceptable time (15 minutes on CPU), unlike previous works which are either expensive, require manual intervention, assume given pattern, geometry or appearance, or strictly control camera and light conditions.Computer Graphics ForumReconstruction from Close-up Image44
A Wave-optics BSDF for Correlated Scatterers
No full textWe present a wave-optics-based BSDF for simulating the corona effect observed when viewing strong light sources through materials such as certain fabrics or glass surfaces with condensation. These visual phenomena arise from the interference of diffraction patterns caused by correlated, disordered arrangements of droplets or pores. Our method leverages the pair correlation function (PCF) to decouple the spatial relationships between scatterers from the diffraction behavior of individual scatterers. This two-level decomposition allows us to derive a physically based BSDF that provides explicit control over both scatterer shape and spatial correlation. We also introduce a practical importance sampling strategy for integrating our BSDF within a Monte Carlo renderer. Our simulation results and real-world comparisons demonstrate that the method can reliably reproduce the characteristics of the corona effects in various real-world diffractive materials.Computer Graphics ForumBSDF Models and Scattering44
Increasing Heritage Accessibility Through Sustainable Digital Content Standards
No full textThis workshop focuses on increasing heritage accessibility through sustainable digital content standards, sharing expertise to discuss 3D Web standards like Web3D and IIIF. Enhancing skills for creating inclusive, sustainable digital content, and exploring how standards support heritage data access and sharing, participants will learn about implementing these standards (e.g. X3D, glTF, IIIF), discuss integrating 3D content across cultural heritage spaces, and consider options for using AI in 3D recognition and generation. The goal is to help in leveraging standards for accessible, sustainable experiences.Digital HeritageWorkshop
Bridging Disciplines for Heritage Professionals: The H2IOSC Digital Training Platform (by CLARIN, DARIAH, E-RIHS and OPERAS)
No full textThe complexity of the contemporary heritage field requires professionals to develop interdisciplinary skills and to collaborate across diverse disciplines, from social sciences and digital humanities to preservation of cultural heritage, archaeology and beyond. As digital and interactive tools become increasingly integrated into heritage studies, the training in the field is undergoing a significant transformation. The H2IOSC (Heritage and Humanities Italian Open Science Cloud) project has developed an innovative digital training infrastructure aimed at providing access to FAIR (Findable, Accessible, Interoperable and Reusable) courses and training materials. In this abstract we focus on the H2IOSC training platform, aimed to address the evolving training needs of our disciplinary communities. Created by H2IOSC WP8 (Work Package 8: Training, Engagement and Capacity Building) in collaboration with the E.T.T. S.p.A., it is maintained and hosted by CNR-ILC (Institute of Computational Linguistics ''A. Zampolli''), host institution of CLARIN-IT, with the participation of the national nodes of DARIAH, E-RIHS, and OPERAS. The platform provides a flexible, customizable learning environment designed to support interdisciplinary education and continuous professional development in the Social Sciences, Digital Humanities and Cultural Heritage sectors. The platform features a comprehensive course catalogue containing training courses and modules developed or adapted by the four infrastructures within the H2IOSC project as FAIR training materials, designed for various target knowledge levels, from beginners to advanced learners in heritage and humanities fields. An intuitive dashboard allows users to access materials, track progress and use collaborative tools, including forums, chats, and virtual working groups for networking and communication. The platform incorporates quizzes, simulations, hands-on exercises, and gamification tools, making learning more interactive. Designed for accessibility and inclusivity, it is fully compatible with both desktop and mobile devices, enabling individual learning without geographical or temporal constraints. This paper outlines the development process of the platform, addressing the challenges encountered, the key achievements, and its potential to transform training within the Social Sciences, Digital Humanities and Heritage Sector. We highlight how the design of specialized digital heritage training materials has influenced the development of the Digital Asset Management (DAM) system, particularly its ability to support effective cataloguing, metadata management, and archival of multimedia data. Ultimately, we emphasize the importance of adopting best practices for interdisciplinary learning and explore how digital tools can foster greater collaboration and knowledge exchange across heritage and humanities disciplines.Digital HeritageFrom DH Theory and Principles to Innovative Practice: Participation, Training, and Acces