905 research outputs found

    Interactive Out-Of-Core Texturing Using Point-Sampled Textures

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    International audienceThe visualization of huge 3D objects becomes available on common workstations thanks to highly optimized data-structures and out-of-core frameworks for rendering. However, the editing, and in particular, the texturing of such objects is still a challenging task, since usual methods for optimized rendering are not easily amenable to interactive modification. In this paper, we introduce the idea of point-sampled textures, and show how to interactively texture such a huge model at various scales, without any parameterization. An adaptive in-core point-based approximated geometry is first created by employing an efficient out-of-core point-sampling algorithm. This simplified geometry is then used for an interactive and multi-scale point-based texturing. Finally, a feature-preserving kernel is used to convert the point-based model into a global 3D texture which can be applied back on the initial huge geometry. Our technique thus provides a flexible tool to generate, edit and apply size-independent textures to a wide range of huge 3D objects thanks to point-based methods

    Triangulation of uniform particle systems: its application to the implicit surface texturing

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    Particle systems, as originally presented by Witkin and Heckbert [32], offer an elegant solution to sample implicit surfaces of arbitrary genus, while providing an extremely regular distribution of samples over the surface. In this paper, we present an ef cient technique that uses particle systems to rapidly generate a triangular mesh over an implicit surface, where each triangle is almost equilateral. The major advantage of such a triangulation is that it minimizes the deformations between the mesh and the underlying implicit surface. We exploit this property by using few triangular texture samples mapped in a non-periodic fashion as presented by Neyret and Cani [16]. The result is a pattern-based texturing method that maps homogeneous non-periodic textures to arbitrary implicit surfaces, with almost no deformation

    Real-time transition texture synthesis for terrains.

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    Depicting the transitions where differing material textures meet on a terrain surface presents a particularly unique set of challenges in the field of real-time rendering. Natural landscapes are inherently irregular and composed of complex interactions between many different material types of effectively endless detail and variation. Although consumer grade graphics hardware is becoming ever increasingly powerful with each successive generation, terrain texturing remains a trade-off between realism and the computational resources available. Technological constraints aside, there is still the challenge of generating the texture resources to represent terrain surfaces which can often span many hundreds or even thousands of square kilometres. To produce such textures by hand is often impractical when operating on a restricted budget of time and funding. This thesis presents two novel algorithms for generating texture transitions in realtime using automated processes. The first algorithm, Feature-Based Probability Blending (FBPB), automates the task of generating transitions between material textures containing salient features. As such features protrude through the terrain surface FBPB ensures that the topography of these features is maintained at transitions in a realistic manner. The transitions themselves are generated using a probabilistic process that also dynamically adds wear and tear to introduce high frequency detail and irregularity at the transition contour. The second algorithm, Dynamic Patch Transitions (DPT), extends FBPB by applying the probabilistic transition approach to material textures that contain no salient features. By breaking up texture space into a series of layered patches that are either rendered or discarded on a probabilistic basis, the contour of the transition is greatly increased in resolution and irregularity. When used in conjunction with high frequency detail techniques, such as alpha masking, DPT is capable of producing endless, detailed, irregular transitions without the need for artistic input

    Repeatable texture sampling with interchangeable patches

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    Rendering textures in real-time environments is a key task in computer graphics. This paper presents a new parallel patch-based method which allows repeatable sampling without cache, and does not create visual repetitions. Interchangeable patches of arbitrary shape are prepared in a preprocessing step, such that patches may lie over the boundary of other patches in a repeating tile. This compresses the example texture into an infinite texture map with small memory requirements, suitable for GPU and ray-tracing applications. The quality of textures rendered with this method can be tuned in the offline preprocessing step, and they can then be rendered in times comparable to Wang tiles. Experimental results demonstrate combined benefits in speed, memory requirements, and quality of randomisation when compared to previous methods

    Large-scale point-cloud visualization through localized textured surface reconstruction

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    In this paper, we introduce a novel scene representation for the visualization of large-scale point clouds accompanied by a set of high-resolution photographs. Many real-world applications deal with very densely sampled point-cloud data, which are augmented with photographs that often reveal lighting variations and inaccuracies in registration. Consequently, the high-quality representation of the captured data, i.e., both point clouds and photographs together, is a challenging and time-consuming task. We propose a two-phase approach, in which the first (preprocessing) phase generates multiple overlapping surface patches and handles the problem of seamless texture generation locally for each patch. The second phase stitches these patches at render-time to produce a high-quality visualization of the data. As a result of the proposed localization of the global texturing problem, our algorithm is more than an order of magnitude faster than equivalent mesh-based texturing techniques. Furthermore, since our preprocessing phase requires only a minor fraction of the whole data set at once, we provide maximum flexibility when dealing with growing data sets

    Interactive Out-Of-Core Texturing

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    International audienceInteractive rendering of huge objects becomes available on common workstations thanks to highly optimized data-structures and out-of-core frameworks for rendering. However, interactive editing, and in particular interactive texturing of such objects, is still a challenging task, since the dynamic information added during this editing step would break any highly-optimized data-structures, such as GPU vertex buffers or specific out-of-core representations of huge objects. We propose Point-Sampled Textures (PST) for interactive texturing of large models at various scales without requiring 2D parameterization (complex and expensive for large models). This framework allows the user to interactively set any appearance property of the original object, from per-sample color to complex BRDFs

    TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusion

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    We present TextureDreamer, a novel image-guided texture synthesis method to transfer relightable textures from a small number of input images (3 to 5) to target 3D shapes across arbitrary categories. Texture creation is a pivotal challenge in vision and graphics. Industrial companies hire experienced artists to manually craft textures for 3D assets. Classical methods require densely sampled views and accurately aligned geometry, while learning-based methods are confined to category-specific shapes within the dataset. In contrast, TextureDreamer can transfer highly detailed, intricate textures from real-world environments to arbitrary objects with only a few casually captured images, potentially significantly democratizing texture creation. Our core idea, personalized geometry-aware score distillation (PGSD), draws inspiration from recent advancements in diffuse models, including personalized modeling for texture information extraction, variational score distillation for detailed appearance synthesis, and explicit geometry guidance with ControlNet. Our integration and several essential modifications substantially improve the texture quality. Experiments on real images spanning different categories show that TextureDreamer can successfully transfer highly realistic, semantic meaningful texture to arbitrary objects, surpassing the visual quality of previous state-of-the-art.Comment: Project page: https://texturedreamer.github.i

    Hierarchical processing, editing and rendering of acquired geometry

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    La représentation des surfaces du monde réel dans la mémoire d’une machine peut désormais être obtenue automatiquement via divers périphériques de capture tels que les scanners 3D. Ces nouvelles sources de données, précises et rapides, amplifient de plusieurs ordres de grandeur la résolution des surfaces 3D, apportant un niveau de précision élevé pour les applications nécessitant des modèles numériques de surfaces telles que la conception assistée par ordinateur, la simulation physique, la réalité virtuelle, l’imagerie médicale, l’architecture, l’étude archéologique, les effets spéciaux, l’animation ou bien encore les jeux video. Malheureusement, la richesse de la géométrie produite par ces méthodes induit une grande, voire gigantesque masse de données à traiter, nécessitant de nouvelles structures de données et de nouveaux algorithmes capables de passer à l’échelle d’objets pouvant atteindre le milliard d’échantillons. Dans cette thèse, je propose des solutions performantes en temps et en espace aux problèmes de la modélisation, du traitement géométrique, de l’édition intéractive et de la visualisation de ces surfaces 3D complexes. La méthodologie adoptée pendant l’élaboration transverse de ces nouveaux algorithmes est articulée autour de 4 éléments clés : une approche hiérarchique systématique, une réduction locale de la dimension des problèmes, un principe d’échantillonage-reconstruction et une indépendance à l’énumération explicite des relations topologiques aussi appelée approche basée-points. En pratique, ce manuscrit propose un certain nombre de contributions, parmi lesquelles : une nouvelle structure hiérarchique hybride de partitionnement, l’Arbre Volume-Surface (VS-Tree) ainsi que de nouveaux algorithmes de simplification et de reconstruction ; un système d’édition intéractive de grands objets ; un noyau temps-réel de synthèse géométrique par raffinement et une structure multi-résolution offrant un rendu efficace de grands objets. Ces structures, algorithmes et systèmes forment une chaîne capable de traiter les objets en provenance du pipeline d’acquisition, qu’ils soient représentés par des nuages de points ou des maillages, possiblement non 2-variétés. Les solutions obtenues ont été appliquées avec succès aux données issues des divers domaines d’application précités.Digital representations of real-world surfaces can now be obtained automatically using various acquisition devices such as 3D scanners and stereo camera systems. These new fast and accurate data sources increase 3D surface resolution by several orders of magnitude, borrowing higher precision to applications which require digital surfaces. All major computer graphics applications can take benefit of this automatic modeling process, including: computer-aided design, physical simulation, virtual reality, medical imaging, architecture, archaeological study, special effects, computer animation and video games. Unfortunately, the richness of the geometry produced by these media comes at the price of a large, possibility gigantic, amount of data which requires new efficient data structures and algorithms offering scalability for processing such objects. This thesis proposes time and space efficient solutions for modeling, editing and rendering such complex surfaces, solving these problems with new algorithms sharing 4 fundamental elements: a systematic hierarchical approach, a local dimension reduction, a sampling-reconstruction paradigm and a pointbased basis. Basically, this manuscript proposes several contributions, including: a new hierarchical space subdivision structure, the Volume-Surface Tree, for geometry processing such as simplification and reconstruction; a streaming system featuring new algorithms for interactive editing of large objects, an appearancepreserving multiresolution structure for efficient rendering of large point-based surfaces, and a generic kernel for real-time geometry synthesis by refinement. These elements form a pipeline able to process acquired geometry, either represented by point clouds or non-manifold meshes. Effective results have been successfully obtained with data coming from the various applications mentioned
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