2,440 research outputs found

    Real-time Realistic Rain Rendering

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    Artistic outdoor filming and rendering need to choose specific weather conditions in order to properly trigger the audience reaction; for instance, rain, one of the most common conditions, is usually employed to transmit a sense of unrest. Synthetic methods to recreate weather are an important avenue to simplify and cheapen filming, but simulations are a challenging problem due to the variety of different phenomena that need to be computed. Rain alone involves raindrops, splashes on the ground, fog, clouds, lightnings, etc. We propose a new rain rendering algorithm that uses and extends present state of the art approaches in this field. The scope of our method is to achieve real-time renders of rain streaks and splashes on the ground, while considering complex illumination effects and allowing an artistic direction for the drops placement. Our algorithm takes as input an artist-defined rain distribution and density, and then creates particles in the scene following these indications. No restrictions are imposed on the dimensions of the rain area, thus direct rendering approaches could rapidly overwhelm current computational capabilities with huge particle amounts. To solve this situation, we propose techniques that, in rendering time, adaptively sample the particles generated in order to only select the ones in the regions that really need to be simulated and rendered. Particle simulation is executed entirely in the graphics hardware. The algorithm proceeds by placing the particles in their updated coordinates. It then checks whether a particle is falling as a rain streak, it has reached the ground and it is a splash or, finally, if it should be discarded because it has entered a solid object of the scene. Different rendering techniques are used for each case. Complex illumination parameters are computed for rain streaks to select textures matching them. These textures are generated in a preprocess step and realistically simulate light when interacting with the optical properties of the water drops

    Realistic natural atmospheric phenomena and weather effects for interactive virtual environments.

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    Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physicallybased simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation

    Real-time Realistic Rain Rendering

    Get PDF
    Artistic outdoor filming and rendering need to choose specific weather conditions in order to properly trigger the audience reaction; for instance, rain, one of the most common conditions, is usually employed to transmit a sense of unrest. Synthetic methods to recreate weather are an important avenue to simplify and cheapen filming, but simulations are a challenging problem due to the variety of different phenomena that need to be computed. Rain alone involves raindrops, splashes on the ground, fog, clouds, lightnings, etc. We propose a new rain rendering algorithm that uses and extends present state of the art approaches in this field. The scope of our method is to achieve real-time renders of rain streaks and splashes on the ground, while considering complex illumination effects and allowing an artistic direction for the drops placement. Our algorithm takes as input an artist-defined rain distribution and density, and then creates particles in the scene following these indications. No restrictions are imposed on the dimensions of the rain area, thus direct rendering approaches could rapidly overwhelm current computational capabilities with huge particle amounts. To solve this situation, we propose techniques that, in rendering time, adaptively sample the particles generated in order to only select the ones in the regions that really need to be simulated and rendered. Particle simulation is executed entirely in the graphics hardware. The algorithm proceeds by placing the particles in their updated coordinates. It then checks whether a particle is falling as a rain streak, it has reached the ground and it is a splash or, finally, if it should be discarded because it has entered a solid object of the scene. Different rendering techniques are used for each case. Complex illumination parameters are computed for rain streaks to select textures matching them. These textures are generated in a preprocess step and realistically simulate light when interacting with the optical properties of the water drops

    CATRA: Interactive Measuring and Modeling of Cataracts

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    We introduce an interactive method to assess cataracts in the human eye by crafting an optical solution that measures the perceptual impact of forward scattering on the foveal region. Current solutions rely on highly-trained clinicians to check the back scattering in the crystallin lens and test their predictions on visual acuity tests. Close-range parallax barriers create collimated beams of light to scan through sub-apertures, scattering light as it strikes a cataract. User feedback generates maps for opacity, attenuation, contrast and sub-aperture point-spread functions. The goal is to allow a general audience to operate a portable high-contrast light-field display to gain a meaningful understanding of their own visual conditions. User evaluations and validation with modified camera optics are performed. Compiled data is used to reconstruct the individual's cataract-affected view, offering a novel approach for capturing information for screening, diagnostic, and clinical analysis.Alfred P. Sloan Foundation (Research Fellowship)United States. Defense Advanced Research Projects Agency (Young Faculty Award

    An approximation to multiple scattering in volumetric illumination towards real-time rendering

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    Many volumetric illumination techniques for volume rendering were developed through out the years. However, there are still many constraints regarding the computation of multiple scattering path tracing in real-time applications due to its natural complexity and scale. Path tracing with multiple scattering support can produce physically correct results but suffers from noise and low convergence rates. This work proposes a new real-time algorithm to approximate multiple scattering, usually only available in offline rendering production, to real-time. Our approach explores the human perceptual system to speed up computation. Given two images, we use a CIE metric stating that the two will be perceived as similar to the human eye if the Euclidean distance between the two images in CIELAB color space is smaller than 2.3. Hence, we use this premise to guide our in vestigations when changing ray and bounce parameters in our renderer. Our results show that we can reduce from 105 to 104 Samples Per Pixel (SPP) with a negligible perceptual difference between both results, allowing us to cut rendering times by 10 whenever we divide SPP by 10. Similarly, we can reduce the number of bounces from 1000 to 100 with a negligible perceptual difference while reducing rendering times by almost half. We also propose a new algorithm in real-time, Lobe Estimator, that approximates these behaviors and parameters while performing twice as faster as the classic Ray Marching technique.Muitas técnicas de ilmuninação volumétrica foram desenvolvidas ao longo dos anos. Entretanto, ainda há muitas restrições na computação de multiple scattering em aplicações de tempo real usando path tracing, devido à sua complexidade e escala. Path tracing com suporte a multiple scattering é capaz de produzir resultados fisicamente corretos, mas sofre de ruídos e baixa taixa de convergência. Portanto, este trabalho propõe um novo algoritmo de tempo real para aproximar multiple scattering, usado em offline rendering. Nossa abordagem irá explorar o sistema perceptual visual humano para acelerar a computação. A partir de duas imagens, nós usamos a métrica da CIE que afirma que duas imagens são percebidas como similar ao olho humano se a distância Euclidiana das duas imagens no espaço de cores CIELAB for menor que 2.3. Dessa forma, nós usamos essa premissa para guiar nossas investigações quando alterando os parâmetros de Samples Per Pixel (SPP) e bounces nos renderizadores. Nossos resultados mostram que podemos redu zir de 105 para 104 Samples Per Pixel (SPP) com uma diferença perceptual negligenciável entre ambos paramêtros, permitindo reduzir o tempo de renderização por 10 a cada vez que dividimos o SPP por 10. Similarmente, nós podemos reduzir o número de bounces de 1000 para 100 com uma diferença perceptual negligenciável, enquanto reduzindo o tempo de renderização por quase metade. Nós também propusemos um novo algoritmo em tempo real, Lobe Estimator, que permite aproximar esses comportamentos e paramê tros enquanto permformando duas vezes mais rápido que o clássico Ray Marching

    Large-scale cloudscapes using noise

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    Clouds have been of particular interest in computer graphics due to the challenge they present. Clouds are considered fuzzy objects, and need specialized algorithms to model and render realistically. Many techniques exist to model and render clouds that have had much success. This research will take existing techniques in cloud modeling and rendering and create a new technique combining those with noise. The idea is that noise can be used to model large-scale repeatable 3D cloudscapes and to be able to model such cloudscapes much more quickly than current techniques. This would be beneficial to developers of virtual universes that have very many worlds numbering in the ten to hundreds to create convincing cloudscapes on each distinct world

    Realistic simulation and animation of clouds using SkewT-LogP diagrams

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    Nuvens e clima são tópicos importantes em computação gráfica, nomeadamente na simulação e animação de fenómenos naturais. Tal deve-se ao facto de a simulação de fenómenos naturais−onde as nuvens estão incluídas−encontrar aplicações em filmes, jogos e simuladores de voo. Contudo, as técnicas existentes em computação gráfica apenas permitem representações de nuvens simplificadas, tornadas possíveis através de dinâmicas fictícias que imitam a realidade. O problema que este trabalho pretende abordar prende-se com a simulação de nuvens adequadas para utilização em ambientes virtuais, isto é, nuvens com dinâmica baseada em física que variam ao longo do tempo. Em meteorologia é comum usar técnicas de simulação de nuvens baseadas em leis da física, contudoossistemasatmosféricosdeprediçãonuméricasãocomputacionalmente pesados e normalmente possuem maior precisão numérica do que o necessário em computação gráfica. Neste campo, torna-se necessário direcionar e ajustar as características físicas ou contornar a realidade de modo a atingir os objetivos artísticos, sendo um fator fundamental que faz com que a computação gráfica se distinga das ciências físicas. Contudo, simulações puramente baseadas em física geram soluções de acordo com regras predefinidas e tornam-se notoriamente difíceis de controlar. De modo a enfrentar esses desafios desenvolvemos um novo método de simulação de nuvens baseado em física que possui a característica de ser computacionalmente leve e simula as propriedades dinâmicas relacionadas com a formação de nuvens. Este novo modelo evita resolver as equações físicas, ao apresentar uma solução explícita para essas equações através de diagramas termodinâmicos SkewT/LogP. O sistema incorpora dados reais de forma a simular os parâmetros necessários para a formação de nuvens. É especialmente adequado para a simulação de nuvens cumulus que se formam devido ao um processo convectivo. Esta abordagem permite não só reduzir os custos computacionais de métodos baseados em física, mas também fornece a possibilidade de controlar a forma e dinâmica de nuvens através do controlo dos níveis atmosféricos existentes no diagrama SkewT/LogP. Nestatese,abordámostambémumoutrodesafio,queestárelacionadocomasimulação de nuvens orográficas. Do nosso conhecimento, esta é a primeira tentativa de simular a formação deste tipo de nuvens. A novidade deste método reside no fato de este tipo de nuvens serem não convectivas, oque se traduz nocálculodeoutrosníveis atmosféricos. Além disso, atendendo a que este tipo de nuvens se forma sobre montanhas, é também apresentadoumalgoritmoparadeterminarainfluênciadamontanhasobreomovimento da nuvem. Em resumo, esta dissertação apresenta um conjunto de algoritmos para a modelação e simulação de nuvens cumulus e orográficas, recorrendo a diagramas termodinâmicos SkewT/LogP pela primeira vez no campo da computação gráfica.Clouds and weather are important topics in computer graphics, in particular in the simulation and animation of natural phenomena. This is so because simulation of natural phenomena−where clouds are included−find applications in movies, games and flight simulators. However, existing techniques in computer graphics only offer the simplified cloud representations, possibly with fake dynamics that mimic the reality. The problem that this work addresses is how to find realistic simulation of cloud formation and evolution, that are suitable for virtual environments, i.e., clouds with physically-based dynamics over time. It happens that techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems based on physics laws are computationally expensive and provide more numerical accuracy than the required accuracy in computer graphics. In computer graphics, we often need to direct and adjust physical features, or even to bend the reality, to meet artistic goals, which is a key factor that makes computer graphics distinct from physical sciences. However, pure physically-based simulations evolve their solutions according to pre-set physics rules that are notoriously difficult to control. In order to face these challenges we have developed a new lightweight physically-based cloudsimulationschemethatsimulatesthedynamicpropertiesofcloudformation. This new model avoids solving the physically-based equations typically used to simulate the formation of clouds by explicitly solving these equations using SkewT/LogP thermodynamic diagrams. The system incorporates a weather model that uses real data to simulate parameters related to cloud formation. This is specially suitable to the simulation of cumulus clouds, which result from a convective process. This approach not only reduces the computational costs of previous physically-based methods, but also provides a technique to control the shape and dynamics of clouds by handling the cloud levels in SkewT/LogP diagrams. In this thesis, we have also tackled a new challenge, which is related to the simulation oforographic clouds. From ourknowledge, this isthefirstattempttosimulatethis type of cloud formation. The novelty in this method relates to the fact that these clouds are non-convective, so that different atmospheric levels have to be determined. Moreover, since orographic clouds form over mountains, we have also to determine the mountain influence in the cloud motion. In summary, this thesis presents a set of algorithms for the modelling and simulation of cumulus and orographic clouds, taking advantage of the SkewT/LogP diagrams for the first time in the field of computer graphics

    SOL-NeRF:Sunlight Modeling for Outdoor Scene Decomposition and Relighting

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    Outdoor scenes often involve large-scale geometry and complex unknown lighting conditions, making it difficult to decompose them into geometry, reflectance and illumination. Recently researchers made attempts to decompose outdoor scenes using Neural Radiance Fields (NeRF) and learning-based lighting and shadow representations. However, diverse lighting conditions and shadows in outdoor scenes are challenging for learning-based models. Moreover, existing methods may produce rough geometry and normal reconstruction and introduce notable shading artifacts when the scene is rendered under a novel illumination. To solve the above problems, we propose SOL-NeRF to decompose outdoor scenes with the help of a hybrid lighting representation and a signed distance field geometry reconstruction. We use a single Spherical Gaussian (SG) lobe to approximate the sun lighting, and a first-order Spherical Harmonic (SH) mixture to resemble the sky lighting. This hybrid representation is specifically designed for outdoor settings, and compactly models the outdoor lighting, ensuring robustness and efficiency. The shadow of the direct sun lighting can be obtained by casting the ray against the mesh extracted from the signed distance field, and the remaining shadow can be approximated by Ambient Occlusion (AO). Additionally, sun lighting color prior and a relaxed Manhattan-world assumption can be further applied to boost decomposition and relighting performance. When changing the lighting condition, our method can produce consistent relighting results with correct shadow effects. Experiments conducted on our hybrid lighting scheme and the entire decomposition pipeline show that our method achieves better reconstruction, decomposition, and relighting performance compared to previous methods both quantitatively and qualitatively.</p
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