StyleDEM: a Versatile Model for Authoring Terrains

Many terrain modelling methods have been proposed for the past decades, providing efficient and often interactive authoring tools. However, they generally do not include any notion of style, which is a critical aspect for designers in the entertainment industry. We introduce StyleDEM, a new generative adversarial network method for terrain synthesis and authoring, with a versatile toolbox of authoring methods with style. This method starts from an input sketch or an existing terrain. It outputs a terrain with features that can be authored using interactive brushes and enhanced with additional tools such as style manipulation or super-resolution. The strength of our approach resides in the versatility and interoperability of the toolbox

Procedural modelling of terrains with constraints

Terrain is an essential part of any outdoor environment and, consequently, many techniques have appeared that deal with the problem of its automatic generation, such as procedural modeling. One form to create terrains is using noise functions because its low computational cost and its random result. However, the randomness of these functions also makes it difficult to have any control over the result obtained. In order to solve the problem of lack of control, this paper presents a new method noise-based that allows procedural terrains creation with elevation constraints (GPS routes, points of interest and areas of interest). For this, the method establishes the restrictions as fixed values in the heightmap function and creates a system of equations to obtain all points that they depend this restrictions. In this way, the terrain obtained maintains the random noise, but including the desired restrictions. The paper also includes how we apply this method on large terrain models without losing resolution or increasing the computational cost excessively. The results show that our method makes it possible to integrate this kind of constraints with high accuracy and realism while preserving the natural appearance of the procedural generation

Modélisation de terrains par primitives

National audienceNous proposons un modèle de terrain hiérarchique et compact permettant de représenter des scènes complexes. Ce modèle de représentation s'inspire des surfaces implicites à squelettes et définit une fonction d'élévation sous la forme d'un arbre de construction. Les feuilles sont des primitives décrivant des morceaux de terrains à différentes échelles (montagnes, fleuves, ...) et les noeuds internes sont des opérateurs de combinaison. L'élévation d'un point est calculée en traversant la structure d'arbre et en combinant les contributions de chaque primitive. La définition des feuilles et des opérateurs garantit que la fonction d'élévation résultante est Lipschitzienne, ce qui permet d'accélérer les calculs de visualisation en utilisant un algorithme de sphere tracing. Mots Clés : modélisation de terrains, phénomènes naturels, modélisation procédurale, surface implicite We propose a compact hierarchical procedural model that combines feature-based primitives to create complex continuous terrains. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation by using a construction tree whose leaves are primitives describing terrain fragments, and whose inner nodes include operations that combine its sub-trees. The elevation of a point is evaluated by traversing the tree and by combining the contributions of each primitive. The definition of both leaves and operators guarantees that the resulting elevation function is Lipschitz which enables us to speed up sphere tracing and surface adaptive tesselation algorithms

Microbial content generation for natural terrains in computer games

Procedural content generation (PCG) has been applied since several decades to fulfill various game-related design needs. Besides bio-inspired methods, living (non-human) organisms were used in computer games for various purposes, such as behavior generation, data gathering, and player education. No living organisms were used for the generation of virtual terrains in games. Such an approach to terrain generation could benefit from morphological similarity between natural terrains and colonies of microbial organisms, real-time development of terrains over time, and educational opportunities. We successfully executed an experiment in which we used growing bacterial and fungal cultures for generating naturally appearing virtual terrains in real-time. Concludingly, we confirm the feasibility of using living organisms in real-time non-behavioral PCG and reflect on its potential impact.Computer Systems, Imagery and Medi

Juntando Modelação 3D Manual e Procedimental

Na área da modelação tridimensional existem duas grandes vertentes: modelação manual e modelação procedimental. Na primeira, o utilizador modela o objeto interagindo diretamente com o resultado através de ferramentas virtuais que, em alguns casos, se aproximam daquelas utilizadas por modeladores em objetos reais; desta forma permitindo um controlo direto e fino sobre o que está a ser produzido. Em modelação procedimental, os objetos são construídos de forma automática a partir de várias condições definidas pelo utilizador, através de regras textuais numa linguagem dedicada ou de grafos de fluxo de dados, permitindo um produção rápida em em grandes quantidades de conteúdo 3D.No entanto, nem sempre a interação com estes métodos é a mais intuitiva. Em situações em que é necessário introduzir detalhes particulares, o processo de criação procedimental torna-se demasiado trabalhoso. Para esses casos, a modelação manual seria a mais adequada para efetuar correções ou ajustes em detalhes.É assim importante encontrar um meio que permita combinar as vantagens da modelação manual com as vantagens da modelação procedimental, para que os potenciais utilizadores possam criar modelos tridimensionais com maior eficiência. Esta dissertação têm como objetivo avaliar possíveis abordagens de integração das duas vertentes de modelação e o impacto da respetiva utilização. Para tal, foi implementada e testada uma solução que visa integrar a ferramenta de modelação procedimental Construct na ferramenta de modelação manual Blender.The domain of tridimensional modelling contains two major approaches: manual modelling and procedural modeling.In the first, the user models the object interacting directly with the result through virtual tools which, in some cases, work similarly to those utilized by modelers in real objects; thus allowing for direct and rigorous control over what is being produced. In procedural modelling, the objects are created automatically through several user-defined conditions, by textual rules in a dedicated language or data-flow graphs, allowing for quick and large-scale production of 3D content.On the other hand, interaction with these methods isn't always the most intuitive. In cases where it's necessary to introduce particular details, the procedural generation process becomes too taxing. For those situations, manual modelling would be the most adequate to perform corrections or small adjustments over details.So, it is important to find a medium which permits combining the advantages of manual modelling with those of procedural modelling, so that potential users may create tridimensional models with greater efficiency.This dissertation has as its objective the evaluation of possible integrations of the two main approaches of 3D modelling and the impact of the corresponding usage. To that purpose, a solution that aims to integrate the procedural modelling tool Construct in the manual modelling tool Blender was implemented and tested

Water wave animation via wavefront parameter interpolation

We present an efficient wavefront tracking algorithm for animating bodies of water that interact with their environment. Our contributions include: a novel wavefront tracking technique that enables dispersion, refraction, reflection, and diffraction in the same simulation; a unique multivalued function interpolation method that enables our simulations to elegantly sidestep the Nyquist limit; a dispersion approximation for efficiently amplifying the number of simulated waves by several orders of magnitude; and additional extensions that allow for time-dependent effects and interactive artistic editing of the resulting animation. Our contributions combine to give us multitudes more wave details than similar algorithms, while maintaining high frame rates and allowing close camera zooms

Automatic evolution of programs for procedural generation of terrains for video games: accessibility and edge length constraints

Nowadays the video game industry is facing a big challenge: keep costs under control as games become bigger and more complex. Creation of game content, such as character models, maps, levels, textures, sound effects and so on, represent a big slice of total game production cost. Hence, the video game industry is increasingly turning to procedural content generation to amplify the cost-effectiveness of the efforts of video game designers. However, procedural methods for automated content generation are difficult to create and parametrize. In this work we study a Genetic Programming based procedural content technique to generate procedural terrains that do not require parametrization, thus, allowing to save time and help reducing production costs. Generated procedural terrains present aesthetic appeal; however, unlike most techniques involving aesthetic, our approach does not require a human to perform the evaluation. Instead, the search is guided by the weighted sum of two morphological metrics: terrain accessibility and obstacle edge length. The combination of the two metrics allowed us to find a wide range of fit terrains that present more scattered obstacles in different locations, than our previous approach with a single metric. Procedural terrains produced by this technique are already in use in a real video game

3D terrain generation using neural networks

With the increase in computation power, coupled with the advancements in the field in the form of GANs and cGANs, Neural Networks have become an attractive proposition for content generation. This opened opportunities for Procedural Content Generation algorithms (PCG) to tap Neural Networks generative power to create tools that allow developers to remove part of creative and developmental burden imposed throughout the gaming industry, be it from investors looking for a return on their investment and from consumers that want more and better content, fast. This dissertation sets out to develop a PCG mixed-initiative tool, leveraging cGANs, to create authored 3D terrains, allowing users to directly influence the resulting generated content without the need for formal training on terrain generation or complex interactions with the tool to influence the generative output, as opposed to state of the art generative algorithms that only allow for random content generation or are needlessly complex. Testing done to 113 people online, as well as in-person testing done to 30 people, revealed that it is indeed possible to develop a tool that allows users from any level of terrain creation knowledge, and minimal tool training, to easily create a 3D terrain that is more realistic looking than those generated by state-of-the-art solutions such as Perlin Noise.Com o aumento do poder de computação, juntamente com os avanços neste campo na forma de GANs e cGANs, as Redes Neurais tornaram-se numa proposta atrativa para a geração de conteúdos. Graças a estes avanços, abriram-se oportunidades para os algoritmos de Geração de Conteúdos Procedimentais(PCG) explorarem o poder generativo das Redes Neurais para a criação de ferramentas que permitam aos programadores remover parte da carga criativa e de desenvolvimento imposta em toda a indústria dos jogos, seja por parte dos investidores que procuram um retorno do seu investimento ou por parte dos consumidores que querem mais e melhor conteúdo, o mais rápido possível. Esta dissertação pretende desenvolver uma ferramenta de iniciativa mista PCG, alavancando cGANs, para criar terrenos 3D cocriados, permitindo aos utilizadores influenciarem diretamente o conteúdo gerado sem necessidade de terem formação formal sobre a criação de terrenos 3D ou interações complexas com a ferramenta para influenciar a produção generativa, opondo-se assim a algoritmos generativos comummente utilizados, que apenas permitem a geração de conteúdo aleatório ou que são desnecessariamente complexos. Um conjunto de testes feitos a 113 pessoas online e a 30 pessoas presencialmente, revelaram que é de facto possível desenvolver uma ferramenta que permita aos utilizadores, de qualquer nível de conhecimento sobre criação de terrenos, e com uma formação mínima na ferramenta, criar um terreno 3D mais realista do que os terrenos gerados a partir da solução de estado da arte, como o Perlin Noise, e de uma forma fácil