Abstract Real‐time by‐example texture synthesis is used in interactive virtual worlds to generate the appearance of an unbounded surface from an exemplar texture with as few repetitions as possible. Currently, leading real‐time methods rely on a tiling and blending scheme which is known to synthesize well texture patterns with little spatial organization (such as random scratches or noise) or patterns with periodic spatial organization (such as brick walls or regular tilings). However, attempting to synthesize texture patterns composed of distinct, non‐periodic regions with such methods remains a challenge and can lead to visual artifacts. In this paper, we propose a novel texture synthesis method to address this issue. The key of our technique relies on the observation that exchanging the appearance of periodically tiled regions is sufficient to hide repetition artifacts. We therefore present a synthesis scheme that relies on the real‐time exchange of local statistics, including means, covariance matrices, or histograms. Since our target texture is evaluated on the fly, naive filtering schemes relying on precomputation, such as direct MIP‐mapping, do not provide accurate results. Therefore, we propose an adequate real‐time filtering approximation and show that our method produces high‐quality results with little artifacts and a GPU‐friendly implementation.

Abstract Real‐time rendering of complex environments and detailed objects is challenging due to the geometric generation cost and its associated memory requirements. Traditional methods often rely on precomputed procedural details, limiting flexibility and realtime interaction. Although state‐of‐the‐art approaches have addressed these questions, they frequently fall short in providing dynamic, high‐fidelity surface transformations. This article presents a novel real‐time procedural mesh resurfacing method that utilizes GPU mesh shaders to generate a wide range of geometrical appearances directly in place of a base control mesh. Our approach enables on‐the‐fly procedural geometry generation, allowing for the creation of new explicit geometric surfaces, fine control over geometric adjustments, and dynamic level of detail management. Procedural parameters can be accurately driven in real time by explicit control maps or arbitrary user inputs. The proposed technique reduces VRAM usage and power consumption, offering competitive performance compared to traditional pipelines. Comparative evaluations demonstrate that it enables a significantly higher number of primitives to be rendered in real‐time without being limited by GPU memory. The key advantage of the proposed resurfacing framework lies in its ability to fully control dynamic generation of surfaces at rendertime.

While precise spectral control can be achieved through sparse convolution, corresponding state of the art noise models are typically too expensive for solid noise. We introduce an alternative, wave-based procedural noise model, fast enough to be used in any dimension. We express the noise in the spectral domain and then apply an inverse Fourier transform (FT), requiring the computation of a multidimensional integral. Our contribution is a novel, efficient way to perform this computation, using a sum of precomputed complex-valued hyperplanar wave-functions, oriented in random directions. We show that using suitable wave profiles and combination operators, our model is able to extend to 3D a number of Gaussian and non-Gaussian noises, including Gabor, by-example and Phasor noises, as well as generate novel cellular noises. Our versatile and controllable solid noise model is very compact, a key feature for complex power spectrum and animated noises. We illustrate this through the design of 2D, 3D, and 3D+t materials using color, transparency and style transfer functions.

This paper aims at rendering interactive visual effects inherent to complex interactions between trees and rain in real-time in order to increase the realism of natural rainy scenes. Such a complex phenomenon involves a great number of physical processes influenced by various interlinked factors and its rendering represents a thorough challenge in Computer Graphics. We approach this problem by introducing an original method to render drops dripping from leaves after interception of raindrops by foliage. Our method introduces a new hydrological model representing interactions between rain and foliage through a phenomenological approach. Our model reduces the complexity of the phenomenon by representing multiple dripping drops with a new fully functional form evaluated per-pixel on-the-fly and providing improved control over density and physical properties. Furthermore, an efficient real-time rendering scheme, taking full advantage of latest GPU hardware capabilities, allows the rendering of a large number of dripping drops even for complex scenes.

Local random-phase noise is a noise model for procedural texturing. It is defined on a regular spatial grid by local noises, which are sums of cosines with random phase. Our model is versatile thanks to separate sampling in the spatial and spectral domains. Therefore, it encompasses Gabor noise and noise by Fourier series. A stratified spectral sampling allows for a faithful yet compact and efficient reproduction of an arbitrary power spectrum. Noise by example is therefore obtained faster than state-of-the-art techniques. As a second contribution we address texture by example and generate not only Gaussian patterns but also structured features present in the input. This is achieved by fixing the phase on some part of the spectrum. Generated textures are continuous and non-repetitive. Results show unprecedented framerates and a flexible visual result: users can control with one parameter the blending between noise by example and structured texture synthesis.

Abstract A procedural pattern generation process, called multi‐scale “assemblage” is introduced. An assemblage is defined as a multi‐scale composition of “multi‐variate” statistical figures, that can be kernel functions for defining noise‐like texture basis functions, or that can be patterns for defining structured procedural textures. This paper presents two main contributions: 1) a new procedural random point distribution function, that, unlike point jittering, allow us to take into account some spatial dependencies among figures and 2) a “multi‐variate” approach that, instead of defining finite sets of constant figures, allows us to generate nearly infinite variations of figures on‐the‐fly. For both, we use a “statistical shape model”, which is a representation of shape variations. Thanks to a direct GPU implementation, assemblage textures can be used to generate new classes of procedural textures for real‐time rendering by preserving all characteristics of usual procedural textures, namely: infinity, definition independency (provided the figures are also definition independent) and extreme compactness.

We introduce procedural texture particles, a new texture model at mid-way between procedural textures and example-based texture synthesis. As for example-based texture synthesis, we use an input example to produce similar looking textures. But instead of creating texture images (pixel arrays), our textures are defined in the form of procedural distributions of interchangeable visual elements called particles. As for classical example-based synthesis, our method guarantees a certain visual resemblance with the example, but obtained textures are compact and defined on the entire infinite 2D plane.

Abstract Noisy volumetric details like clouds, grounds, plaster, bark, roughcast, etc. are frequently encountered in nature and bring an important contribution to the realism of outdoor scenes. We introduce a new interactive approach, easing the creation of procedural representations of “stochastic” volumetric details by using a single example photograph. Instead of attempting to reconstruct an accurate geometric representation from the photograph, we use a stochastic multi‐scale approach that fits parameters of a multi‐layered noise‐based 3D deformation model, using a multi‐resolution filter banks error metric. Once computed, visually similar details can be applied to arbitrary objects with a high degree of visual realism, since lighting and parallax effects are naturally taken into account. Our approach is inspired by image‐based techniques. In practice, the user supplies a photograph of an object covered by noisy details, provides a corresponding coarse approximation of the shape of this object as well as an estimated lighting condition (generally a light source direction). Our system then determines the corresponding noise‐based representation as well as some diffuse, ambient, specular and semi‐transparency reflectance parameters. The resulting details are fully procedural and, as such, have the advantage of extreme compactness, while they can be infinitely extended without repetition in order to cover huge surfaces.

Abstract Hypertexturing can be a powerful way of adding rich geometric details to surfaces at low memory cost by using a procedural three‐dimensional (3D) space distortion. However, this special kind of texturing technique still raises a major problem: the efficient control of the visual result. In this paper, we introduce a framework for interactive hypertexture modelling. This framework is based on two contributions. First, we propose a reformulation of the density modulation function. Our density modulation is based on the notion of shape transfer function. This function, which can be easily edited by users, allows us to control in an intuitive way the visual appearance of the geometric details resulting from the space distortion. Second, we propose to use a hybrid surface and volume‐point‐based representation in order to be able to dynamically hypertexture arbitrary objects at interactive frame rates. The rendering consists in a combined splat‐ and raycasting‐based direct volume rendering technique. The splats are used to model the volumetric object while raycasting allows us to add the details. An experimental study on users shows that our approach improves the design of hypertextures and yet preserves their procedural nature.