Towards interactive global illumination effects via sequential Monte Carlo adaptation

Journal ArticleThis paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context while handling general single-bounce global illumination effects. The radiance estimates computed during the rendering process are cached in an adaptive per-pixel structure that defines dynamic predicate functions for both variance reduction techniques and guarantees well-behaved PDFs, yielding continually increasing efficiencies thanks to a marginal computational overhead

Regression-based {Monte Carlo} integration

© Corentin Salaun, Adrien Gruson, Binh-Son Hua, Toshiya Hachisuka & Gurprit Singh | ACM, (2022). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Graphics, http://dx.doi.org/10.1145/3528223.3530095.Monte Carlo integration is typically interpreted as an estimator of the expected value using stochastic samples. There exists an alternative interpretation in calculus where Monte Carlo integration can be seen as estimating a constant function—from the stochastic evaluations of the integrand—that integrates to the original integral. The integral mean value theorem states that this constant function should be the mean (or expectation) of the integrand. Since both interpretations result in the same estimator, little attention has been devoted to the calculus-oriented interpretation. We show that the calculus-oriented interpretation actually implies the possibility of using a more complex function than a constant one to construct a more efficient estimator for Monte Carlo integration. We build a new estimator based on this interpretation and relate our estimator to control variates with least-squares regression on the stochastic samples of the integrand. Unlike prior work, our resulting estimator is provably better than or equal to the conventional Monte Carlo estimator. To demonstrate the strength of our approach, we introduce a practical estimator that can act as a simple drop-in replacement for conventional Monte Carlo integration. We experimentally validate our framework on various light transport integrals. The code is available at https://github.com/iribis/regressionmc

Rendering de iluminación directa y single-scattering utilizando control variates multidimensionales

En la actualidad, existe una gran demanda de generación de imágenes sintéticas indistinguibles de la realidad. Esta tarea tiene un alto nivel de complejidad, debido a que se requiere la simulación correcta de las interacciones de la luz con una escena virtual, modeladas matemáticamente mediante una integral de alta complejidad cuyo resultado se aproxima mediante técnicas de integración numérica.Los algoritmos más utilizados para abordar el problema de la simulación del transporte de luz están basados en el método de integración de Monte Carlo, que utiliza el muestreo aleatorio de caminos de la luz en la escena. Aunque estos algoritmos permiten generar imágenes fieles a la realidad, introducen ruido visible en los resultados finales debido a su naturaleza estocástica si no se toman suficientes muestras.Existen otros métodos de integración como los de tipo Newton-Cotes, que toman muestras de forma determinista para modelar la señal mediante polinomios. Estos métodos, en casos en los que la iluminación presenta una apariencia suave, son capaces de obtener mejores resultados pero introducen sesgo y artefactos visibles en los resultados que hacen que su uso haya sido menos explorado en el campo de la informática gráfica.En este trabajo, se plantea un algoritmo que combina lo mejor de las estrategias de Monte Carlo y de tipo Newton-Cotes mediante el uso de una técnica de reducción de varianza denominada control variates. Este algoritmo es capaz de obtener mejores resultados que el método estándar de Monte Carlo en escenas que tienen zonas con un transporte de luz suave, manteniendo los detalles de alta frecuencia y un resultado sin sesgo.Se implementan dos aplicaciones diferentes de esta técnica: simulación de iluminación directa, en la que se simula la luz que incide directamente en las superficies desde las fuentes de luz; y simulación de medios participativos, en los que la luz es absorbida y dispersada en su paso por el medio. En ambas aplicaciones, se analizan los resultados en diferentes escenas, comparándolos con los que de otras técnicas y analizando su convergencia a un resultado final.<br /

Utilising path-vertex data to improve Monte Carlo global illumination.

Efficient techniques for photo-realistic rendering are in high demand across a wide array of industries. Notable applications include visual effects for film, entertainment and virtual reality. Less direct applications such as visualisation for architecture, lighting design and product development also rely on the synthesis of realistic and physically based illumination. Such applications assert ever increasing demands on light transport algorithms, requiring the computation of photo-realistic effects while handling complex geometry, light scattering models and illumination. Techniques based on Monte Carlo integration handle such scenarios elegantly and robustly, but despite seeing decades of focused research and wide commercial support, these methods and their derivatives still exhibit undesirable side effects that are yet to be resolved. In this thesis, Monte Carlo path tracing techniques are improved upon by utilizing path vertex data and intermediate radiance contributions readily available during rendering. This permits the development of novel progressive algorithms that render low noise global illumination while striving to maintain the desirable accuracy and convergence properties of unbiased methods. The thesis starts by presenting a discussion into optical phenomenon, physically based rendering and achieving photo realistic image synthesis. This is followed by in-depth discussion of the published theoretical and practical research in this field, with a focus on stochastic methods and modem rendering methodologies. This provides insight into the issues surrounding Monte Carlo integration both in the general and rendering specific contexts, along with an appreciation for the complexities of solving global light transport. Alternative methods that aim to address these issues are discussed, providing an insight into modem rendering paradigms and their characteristics. Thus, an understanding of the key aspects is obtained, that is necessary to build up and discuss the novel research and contributions to the field developed throughout this thesis. First, a path space filtering strategy is proposed that allows the path-based space of light transport to be classified into distinct subsets. This permits the novel combination of robust path tracing and recent progressive photon mapping algorithms to handle each subset based on the characteristics of the light transport in that space. This produces a hybrid progressive rendering technique that utilises the strengths of existing state of the art Monte Carlo and photon mapping methods to provide efficient and consistent rendering of complex scenes with vanishing bias. The second original contribution is a probabilistic image-based filtering and sample clustering framework that provides high quality previews of global illumination whilst remaining aware of high frequency detail and features in geometry, materials and the incident illumination. As will be seen, the challenges of edge-aware noise reduction are numerous and long standing, particularly when identifying high frequency features in noisy illumination signals. Discontinuities such as hard shadows and glossy reflections are commonly overlooked by progressive filtering techniques, however by dividing path space into multiple layers, once again based on utilising path vertex data, the overlapping illumination of varying intensities, colours and frequencies is more effectively handled. Thus noise is removed from each layer independent of features present in the remaining path space, effectively preserving such features

Toward robust and efficient physically-based rendering

Le rendu fondé sur la physique est utilisé pour le design, l'illustration ou l'animation par ordinateur. Ce type de rendu produit des images photo-réalistes en résolvant les équations qui décrivent le transport de la lumière dans une scène. Bien que ces équations soient connues depuis longtemps, et qu'un grand nombre d'algorithmes aient été développés pour les résoudre, il n'en existe pas qui puisse gérer de manière efficace toutes les scènes possibles. Plutôt qu'essayer de développer un nouvel algorithme de simulation d'éclairage, nous proposons d'améliorer la robustesse de la plupart des méthodes utilisées à ce jour et/ou qui sont amenées à être développées dans les années à venir. Nous faisons cela en commençant par identifier les sources de non-robustesse dans un moteur de rendu basé sur la physique, puis en développant des méthodes permettant de minimiser leur impact. Le résultat de ce travail est un ensemble de méthodes utilisant différents outils mathématiques et algorithmiques, chacune de ces méthodes visant à améliorer une partie spécifique d'un moteur de rendu. Nous examinons aussi comment les architectures matérielles actuelles peuvent être utilisées à leur maximum afin d'obtenir des algorithmes plus rapides, sans ajouter d'approximations. Bien que les contributions présentées dans cette thèse aient vocation à être combinées, chacune d'entre elles peut être utilisée seule : elles sont techniquement indépendantes les unes des autres.Physically-based rendering is used for design, illustration or computer animation. It consists in producing photorealistic images by solving the equations which describe how light travels in a scene. Although these equations have been known for a long time and many algorithms for light simulation have been developed, no algorithm exists to solve them efficiently for any scene. Instead of trying to develop a new algorithm devoted to light simulation, we propose to enhance the robustness of most methods used nowadays and/or which can be developed in the years to come. We do this by first identifying the sources of non-robustness in a physically-based rendering engine, and then addressing them by specific algorithms. The result is a set of methods based on different mathematical or algorithmic methods, each aiming at improving a different part of a rendering engine. We also investigate how the current hardware architectures can be used at their maximum to produce more efficient algorithms, without adding approximations. Although the contributions presented in this dissertation are meant to be combined, each of them can be used in a standalone way: they have been designed to be internally independent of each other