A spectral-particle hybrid method for rendering falling snow

Falling snow has the visual property that it is simultaneously a set of discrete 3D particles and a 3D dynamic texture. Capturing the texture properties of falling snow using standard particle systems can, however, require enough particles to severely impact rendering rates. Here we show how to address this limitation by rendering the texture properties directly. We use a standard particle system to generate a relatively sparse set of falling snow flakes for a given scene, and we then composite in a dynamic texture. The texture is generated using a novel image-based spectral synthesis method. The spectrum of falling snow is defined by a dispersion relation in the image plane, derived from linear perspective. The dispersion relation relates image speed, image size, and snowflake depth. In the frequency domain, it relates the wavelength and speed of moving 2D image sinusoids. The parameters of this spectral snow can be varied both across the image and over time. This provides the flexibility to match the direction and speed parameters of the spectral snow to those of the falling particle snow. Camera motion can also be matched. Our method produces visually pleasing results at interactive rendering rates. We demonstrate our approach by adding snow effects to static and dynamic scenes. An extension for creating rain effects is also presented. 1

Physically-based simulation of ice formation

The geometric and optical complexity of ice has been a constant source of wonder and inspiration for scientists and artists. It is a defining seasonal characteristic, so modeling it convincingly is a crucial component of any synthetic winter scene. Like wind and fire, it is also considered elemental, so it has found considerable use as a dramatic tool in visual effects. However, its complex appearance makes it difficult for an artist to model by hand, so physically-based simulation methods are necessary. In this dissertation, I present several methods for visually simulating ice formation. A general description of ice formation has been known for over a hundred years and is referred to as the Stefan Problem. There is no known general solution to the Stefan Problem, but several numerical methods have successfully simulated many of its features. I will focus on three such methods in this dissertation: phase field methods, diffusion limited aggregation, and level set methods. Many different variants of the Stefan problem exist, and each presents unique challenges. Phase field methods excel at simulating the Stefan problem with surface tension anisotropy. Surface tension gives snowflakes their characteristic six arms, so phase field methods provide a way of simulating medium scale detail such as frost and snowflakes. However, phase field methods track the ice as an implicit surface, so it tends to smear away small-scale detail. In order to restore this detail, I present a hybrid method that combines phase fields with diffusion limited aggregation (DLA). DLA is a fractal growth algorithm that simulates the quasi-steady state, zero surface tension Stefan problem, and does not suffer from smearing problems. I demonstrate that combining these two algorithms can produce visual features that neither method could capture alone. Finally, I present a method of simulating icicle formation. Icicle formation corresponds to the thin-film, quasi-steady state Stefan problem, and neither phase fields nor DLA are directly applicable. I instead use level set methods, an alternate implicit front tracking strategy. I derive the necessary velocity equations for level set simulation, and also propose an efficient method of simulating ripple formation across the surface of the icicles

Représentation, modélisation et génération procédurale de terrains

Slides disponiblesSoutenance oral (présentation + questions) disponible sur demandeThis PhD (entitled "Representation, modelisation and procedural generation of terrains") is related to movie and videogames digital content creation, especially natural scenes.Our work is dedicated to handle and to generate landscapes efficently. We propose a new model based on a construction tree inside which the user can handle parts of the terrain intuitively. We also present techniques to efficently visualize such model. Finally, we present a new algorithm for generating large-scale terrains exhibiting hierarchical structures based on their hydrographic networks: elevation is generated in a broad compliance to water-tansport principles without having to resort on costly hydraulic simulations.Cette thèse (qui a pour intitulé "Représentation, modélisation et génération procédurale de terrains") a pour cadre la génération de contenus numériques destinés aux films et aux jeux-vidéos, en particulier les scènes naturelles.Nos travaux visent à représenter et à générer des terrains. Nous proposons, en particulier, un nouveau modèle de représentation qui s'appuie sur un arbre de construction et qui va permettre à l'utilisateur de manipuler des morceaux de terrain de façon intuitive. Nous présentons également des techniques pour visualiser ce modèle avec un maximum d'efficacité. Enfin nous développons un nouvel algorithme de génération de terrains qui construit de très grands reliefs possédant des structures hiérarchiques découlant d'un réseau hydrographique : le relief généré est conforme aux grands principes d'écoulement des eaux sans avoir besoin d'utiliser de coûteuses simulations d'érosion hydrique

Computer Game Innovation

Faculty of Technical Physics, Information Technology and Applied Mathematics. Institute of Information TechnologyWydział Fizyki Technicznej, Informatyki i Matematyki Stosowanej. Instytut InformatykiThe "Computer Game Innovations" series is an international forum designed to enable the exchange of knowledge and expertise in the field of video game development. Comprising both academic research and industrial needs, the series aims at advancing innovative industry-academia collaboration. The monograph provides a unique set of articles presenting original research conducted in the leading academic centres which specialise in video games education. The goal of the publication is, among others, to enhance networking opportunities for industry and university representatives seeking to form R&D partnerships. This publication covers the key focus areas specified in the GAMEINN sectoral programme supported by the National Centre for Research and Development