Visual modeling and simulation of multiscale phenomena

Many large-scale systems seen in real life, such as human crowds, fluids, and granular materials, exhibit complicated motion at many different scales, from a characteristic global behavior to important small-scale detail. Such multiscale systems are computationally expensive for traditional simulation techniques to capture over the full range of scales. In this dissertation, I present novel techniques for scalable and efficient simulation of these large, complex phenomena for visual computing applications. These techniques are based on a new approach of representing a complex system by coupling together separate models for its large-scale and fine-scale dynamics. In fluid simulation, it remains a challenge to efficiently simulate fine local detail such as foam, ripples, and turbulence without compromising the accuracy of the large-scale flow. I present two techniques for this problem that combine physically-based numerical simulation for the global flow with efficient local models for detail. For surface features, I propose the use of texture synthesis, guided by the physical characteristics of the macroscopic flow. For turbulence in the fluid motion itself, I present a technique that tracks the transfer of energy from the mean flow to the turbulent fluctuations and synthesizes these fluctuations procedurally, allowing extremely efficient visual simulation of turbulent fluids. Another large class of problems which are not easily handled by traditional approaches is the simulation of very large aggregates of discrete entities, such as dense pedestrian crowds and granular materials. I present a technique for crowd simulation that couples a discrete per-agent model of individual navigation with a novel continuum formulation for the collective motion of pedestrians. This approach allows simulation of dense crowds of a hundred thousand agents at near-real-time rates on desktop computers. I also present a technique for simulating granular materials, which generalizes this model and introduces a novel computational scheme for friction. This method efficiently reproduces a wide range of granular behavior and allows two-way interaction with simulated solid bodies. In all of these cases, the proposed techniques are typically an order of magnitude faster than comparable existing methods. Through these applications to a diverse set of challenging simulation problems, I demonstrate the benefits of the proposed approach, showing that it is a powerful and versatile technique for the simulation of a broad range of large and complex systems

Temporally Coherent Video Stylization

International audienceThe transformation of video clips into stylized animations remains an active research topic in Computer Graphics. A key challenge is to reproduce the look of traditional artistic styles whilst minimizing distracting flickering and sliding artifacts; i.e. with temporal coherence. This chapter surveys the spectrum of available video stylization techniques, focusing on algorithms encouraging the temporally coherent placement of rendering marks, and discusses the trade-offs necessary to achieve coherence. We begin with flow-based adaptations of stroke based rendering (SBR) and texture advection capable of painting video. We then chart the development of the field, and its fusion with Computer Vision, to deliver coherent mid-level scene representations. These representations enable the rotoscoping of rendering marks on to temporally coherent video regions, enhancing the diversity and temporal coherence of stylization. In discussing coherence, we formalize the problem of temporal coherence in terms of three defined criteria, and compare and contrast video stylization using these

Shallow waters simulation

Dissertação de mestrado integrado em Informatics EngineeringRealistic simulation and rendering of water in real-time is a challenge within the field of computer graphics, as it is very computationally demanding. A common simulation approach is to reduce the problem from 3D to 2D by treating the water surface as a 2D heightfield. When simulating 2D fluids, the Shallow Water Equations (SWE) are often employed, which work under the assumption that the water’s horizontal scale is much greater than it’s vertical scale. There are several methods that have been developed or adapted to model the SWE, each with its own advantages and disadvantages. A common solution is to use grid-based methods where there is the classic approach of solving the equations in a grid, but also the Lattice-Boltzmann Method (LBM) which originated from the field of statistical physics. Particle based methods have also been used for modeling the SWE, namely as a variation of the popular Smoothed-Particle Hydrodynamics (SPH) method. This thesis presents an implementation for real-time simulation and rendering of a heightfield surface water volume. The water’s behavior is modeled by a grid-based SWE scheme with an efficient single kernel compute shader implementation. When it comes to visualizing the water volume created by the simulation, there are a variety of effects that can contribute to its realism and provide visual cues for its motion. In particular, When considering shallow water, there are certain features that can be highlighted, such as the refraction of the ground below and corresponding light attenuation, and the caustics patterns projected on it. Using the state produced by the simulation, a water surface mesh is rendered, where set of visual effects are explored. First, the water’s color is defined as a combination of reflected and transmitted light, while using a Cook- Torrance Bidirectional Reflectance Distribution Function (BRDF) to describe the Sun’s reflection. These results are then enhanced by data from a separate pass which provides caustics patterns and improved attenuation computations. Lastly, small-scale details are added to the surface by applying a normal map generated using noise. As part of the work, a thorough evaluation of the developed application is performed, providing a showcase of the results, insight into some of the parameters and options, and performance benchmarks.Simulação e renderização realista de água em tempo real é um desafio dentro do campo de computação gráfica, visto que é muito computacionalmente exigente. Uma abordagem comum de simulação é de reduzir o problema de 3D para 2D ao tratar a superfície da água como um campo de alturas 2D. Ao simular fluidos em 2D, é frequente usar as equações de águas rasas, que funcionam sobre o pressuposto de que a escala horizontal da água é muito maior que a sua escala vertical. Há vários métodos que foram desenvolvidos ou adaptados para modelar as equações de águas rasas, cada uma com as suas vantagens e desvantagens. Uma solução comum é utilizar métodos baseados em grelhas onde existe a abordagem clássica de resolver as equações numa grelha, mas também existe o método de Lattice Boltzmann que originou do campo de física estatística. Métodos baseados em partículas também já foram usados para modelar as equações de águas rasas, nomeadamente como uma variação do popular método de SPH. Esta tese apresenta uma implementação para simulação e renderização em tempo real de um volume de água com uma superfície de campo de alturas. O comportamento da água é modelado por um esquema de equações de águas rasas baseado na grelha com uma implementação eficiente de um único kernel de compute shader. No que toca a visualizar o volume de água criado pela simulação, existe uma variedade de efeitos que podem contribuir para o seu realismo e fornecer dicas visuais sobre o seu movimento. Ao considerar águas rasas, existem certas características que podem ser destacadas, como a refração do terreno por baixo e correspondente atenuação da luz, e padrões de cáusticas projetados nele. Usando o estado produzido pela simulação, uma malha da superfície da água é renderizada, onde um conjunto de efeitos visuais são explorados. Em primeiro lugar, a cor da água é definida como uma combinação de luz refletida e transmitida, sendo que uma BRDF de Cook-Torrance é usada para descrever a reflexão do Sol. Estes resultados são depois complementados com dados gerados num passo separado que fornece padrões de cáusticas e melhora as computações de atenuação. Por fim, detalhes de pequena escala são adicionados à superfície ao aplicar um mapa de normais gerado com ruído. Como parte do trabalho desenvolvido, é feita uma avaliação detalhada da aplicação desenvolvida, onde é apresentada uma demonstração dos resultados, comentários sobre alguns dos parâmetros e opções, e referências de desempenho

Lagrangian Neural Style Transfer for Fluids

Artistically controlling the shape, motion and appearance of fluid simulations pose major challenges in visual effects production. In this paper, we present a neural style transfer approach from images to 3D fluids formulated in a Lagrangian viewpoint. Using particles for style transfer has unique benefits compared to grid-based techniques. Attributes are stored on the particles and hence are trivially transported by the particle motion. This intrinsically ensures temporal consistency of the optimized stylized structure and notably improves the resulting quality. Simultaneously, the expensive, recursive alignment of stylization velocity fields of grid approaches is unnecessary, reducing the computation time to less than an hour and rendering neural flow stylization practical in production settings. Moreover, the Lagrangian representation improves artistic control as it allows for multi-fluid stylization and consistent color transfer from images, and the generality of the method enables stylization of smoke and liquids likewise.Comment: ACM Transaction on Graphics (SIGGRAPH 2020), additional materials: http://www.byungsoo.me/project/lnst/index.htm

Real-time 3D rendering of water using CUDA

This thesis addresses the real-time simulation of 3D water, both on the CPU and on the GPU. The stable fluids method is extended to 3D, and implemented both on the CPU and on the GPU. The GPU-based implementation is done using the NVIDIA Compute Unified Device Architecture API (Application Programming Interface), shortly CUDA. The stable fluids method requires the use of an iterative sparse linear system solver. Therefore, three solvers were implemented on both CPU and GPU, namely Jacobi, Gauss-Seidel, and Conjugate Gradient solvers. Rendering of water or its velocities, of the moving obstacles, of the static obstacles, and of the world are done using Vertex Buffer Objects (VBOs). In the CPU-based version standard OpenGL VBOs are used, while on the GPU-based version OpenGL-CUDA interoperability VBOs and standard OpenGL VBOs are used