Realistic Real-Time Rendering of Global Illumination and Hair through Machine Learning Precomputations

Over the last decade, machine learning has gained a lot of traction in many areas, and with the advent of new GPU models that include acceleration hardware for neural network inference, real-time applications have also started to take advantage of these algorithms.In general, machine learning and neural network methods are not designed to run at the speeds that are required for rendering in high-performance real-time environments, except for very specific and typically limited uses. For example, several methods have been developed recently for denoising of low quality pathtraced images, or to upsample images rendered at lower resolution, that can run in real-time.This thesis collects two methods that attempt to improve realistic scene rendering in such high-performance environments by using machine learning.Paper I presents a neural network application for compressing surface lightfields into a set of unconstrained spherical gaussians to render surfaces with global illumination in a real-time environment.Paper II describes a filter based on a small convolutional neural network that can be used to denoise hair rendered with stochastic transparency in real time

Real-Time Hair Filtering with Convolutional Neural Networks

Rendering of realistic-looking hair is in general still too costly to do in real-time applications, from simulating the physics to rendering the fine details required for it to look natural, including self-shadowing.We show how an autoencoder network, that can be evaluated in real time, can be trained to filter an image of few stochastic samples, including self-shadowing, to produce a much more detailed image that takes into account real hair thickness and transparency

Juguem amb la Wii!: telemesura d'acceleracions en 3D : desenvolupament d'un projecte informàtic de codi lliure

Treball de recerca realitzat per un alumne d'ensenyament secundari i guardonat amb un Premi CIRIT per fomentar l'esperit científic del Jovent l'any 2009. Aquest treball de recerca és un projecte sobre el disseny i la creació d’un programa informàtic de codi obert amb l’objectiu de mesurar acceleracions en tres dimensions utilitzant el comandament de la wii, també conegut com a wiimote. Per tant, s'ha creat un programa que es connecta amb el wiimote, en rep les dades, les guarda i les representa per analitzar posteriorment diversos tipus de moviments i les seves acceleracions. Per tal de fer això es va aprofitar una biblioteca de funcions de codi obert ja existent que aporta les funcions principals per a la comunicació i control del comandament. El codi obert és un concepte que s’utilitza per als projectes informàtics, el codi dels quals està a la disposició de qui el necessiti. La biblioteca utilitzada està escrita en llenguatge C i per a plataforma Linux, i per tal d’aprofitar-la es va haver d’aprendre a utilitzar tant el llenguatge com la plataforma ja que no s'hi havia treballat mai abans. Gràcies a aquest projecte s'ha tingut la possibilitat de veure el funcionament d’algunes tecnologies alternatives i veure’n els avantatges sobre les convencionals o propietàries. Així doncs, des del punt de vista de l'autor, ha estat útil i enriquidor el fet de realitzar-lo.Research project carried out by a pupil of secondary education and rewarded with a Prize CIRIT to foster the scientific spirit of the Youth in year 2009. This research project is aimed at developing a computer program in open source code to measure accelerations in three dimensional axes using the wii remote, also known as wiimote. For that purpose, it was necessary to devise a program that was able to connect to the wiimote, get information from it and save that information so it could be analyzed. In order to do that, an existing open source functions library was used, which brought in the main functions to control and interact with the wii remote. Open source code is a concept used for those projects whose code is accessible for anyone who may need it. That library is written in C language and for Linux platform, and in order to profit from it, the author had to learn how to use both the language and the platform, both of which he was unfamiliar with until then. Thanks to this project the author have had the opportunity to learn the way some alternative technologies work and to see their advantages over the conventional ones

Spherical Gaussian Light‐field Textures for Fast Precomputed Global Illumination

We describe a method to use Spherical Gaussians with free directions and arbitrary sharpness and amplitude to approximate the precomputed local light field for any point on a surface in a scene. This allows for a high‐quality reconstruction of these light fields in a manner that can be used to render the surfaces with precomputed global illumination in real‐time with very low cost both in memory and performance. We also extend this concept to represent the illumination‐weighted environment visibility , allowing for high‐quality reflections of the distant environment with both surface‐material properties and visibility taken into account. We treat obtaining the Spherical Gaussians as an optimization problem for which we train a Convolutional Neural Network to produce appropriate values for each of the Spherical Gaussians\u27 parameters. We define this CNN in such a way that the produced parameters can be interpolated between adjacent local light fields while keeping the illumination in the intermediate points coherent