Importance driven environment map sampling

In this paper we present an automatic and efficient method for supporting Image Based Lighting (IBL) for bidirectional methods which improves both the sampling of the environment, and the detection and sampling of important regions of the scene, such as windows and doors. These often have a small area proportional to that of the entire scene, so paths which pass through them are generated with a low probability. The method proposed in this paper improves this by taking into account view importance, and modifies the lighting distribution to use light transport information. This also automatically constructs a sampling distribution in locations which are relevant to the camera position, thereby improving sampling. Results are presented when our method is applied to bidirectional rendering techniques, in particular we show results for Bidirectional Path Tracing, Metropolis Light Transport and Progressive Photon Mapping. Efficiency results demonstrate speed up of orders of magnitude (depending on the rendering method used), when compared to other methods

A bidirectional formulation for Walk on Spheres

Poisson’s equations and Laplace’s equations are important linear partial differential equations (PDEs)widely used in many applications. Conventional methods for solving PDEs numerically often need todiscretize the space first, making them less efficient for complex shapes. The random walk on spheresmethod (WoS) is a grid-free Monte-Carlo method for solving PDEs that does not need to discrete thespace. We draw analogies between WoS and classical rendering algorithms, and find that the WoSalgorithm is conceptually identical to forward path tracing.We show that solving the Poisson’s equation is equivalent to solving the Green’s function for everypair of points in the domain. Inspired by similar approaches in rendering, we propose a novel WoSreformulation that operates in the reverse direction. Besides this, using the corrector function enablesus to use control variates to estimate the Green’s function. Implementations of this algorithm showimprovement over classical WoS in solving Poisson’s equation with sparse sources. Our approachopens exciting avenues for future algorithms for PDE estimation which, analogous to light transport,connect WoS walks starting from sensors and sources and combine different strategies for robustsolution algorithms in all cases

Radiation techniques for urban thermal simulation with the Finite Element Method

Modern societies are increasingly organized in cities. In the present times, more than half of the world’s population lives in urban settlements. In this context, architectural and building scale works have the need of extending their scope to the urban environment. One of the main challenges of these times is understanting all the thermal exchanges that happen in the city. The radiative part appears as the less developed one; its characterization and interaction with built structures has gained attention for building physics, architecture and environmental engineering. Providing a linkage between these areas, the emerging field of urban physics has become important for tackling studies of such nature. Urban thermal studies are intrinsically linked to multidisciplinary work approaches. Performing full-scale measurements is hard, and prototype models are difficult to develop. Therefore, computational simulations are essential in order to understand how the city behaves and to evaluate projected modifications. The methodological and algorithmic improvement of simulation is one of the mainlines of work for computational physics and many areas of computer science. The field of computer graphics has addressed the adaptation of rendering algorithms to daylighting using physically-based radiation models on architectural scenes. The Finite Element Method (FEM) has been widely used for thermal analysis. The maturity achieved by FEM software allows for treating very large models with a high geometrical detail and complexity. However, computing radiation exchanges in this context implies a hard computational challenge, and forces to push the limits of existing physical models. Computer graphics techniques can be adapted to FEM to estimate solar loads. In the thermal radiation range, the memory requirements for storing the interaction between the elements grows because all the urban surfaces become radiation sources. In this thesis, a FEM-based methodology for urban thermal analysis is presented. A set of radiation techniques (both for solar and thermal radiation) are developed and integrated into the FEM software Cast3m. Radiosity and ray tracing are used as the main algorithms for radiation computations. Several studies are performed for different city scenes. The FEM simulation results are com-pared with measured temperature results obtained by means of urban thermography. Post-processing techniques are used to obtain rendered thermograms, showing that the proposed methodology pro-duces accurate results for the cases analyzed. Moreover, its good computational performance allows for performing this kind of study using regular desktop PCs.Las sociedades modernas están cada vez más organizadas en ciudades. Más de la mitad de la población mundial vive en asentamientos urbanos en la actualidad. En este contexto, los trabajos a escala arquitectónica y de edificio deben extender su alcance al ambiente urbano. Uno de los mayores desafíos de estos tiempos consiste en entender todos los intercambios térmicos que suceden en la ciudad. La parte radiativa es la menos desarrollada; su caracterización y su interacción con edificaciones ha ganado la atención de la física de edificios, la arquitectura y la ingeniería ambiental. Como herramienta de conexión entre estas áreas, la física urbana es un área que resulta importante para atacar estudios de tal naturaleza. Los estudios térmicos urbanos están intrinsecamente asociados a trabajos multidisciplinarios. Llevar a cabo mediciones a escala real resulta difícil, y el desarrollo de prototipos de menor escala es complejo. Por lo tanto, la simulación computacional es esencial para entender el comportamiento de la ciudad y para evaluar modificaciones proyectadas. La mejora metodológica y algorítmica de las simulaciones es una de las mayores líneas de trabajo para la física computacional y muchas áreas de las ciencias de la computación. El área de la computación gráfica ha abordado la adaptación de algoritmos de rendering para cómputo de iluminación natural, utilizando modelos de radiación basados en la física y aplicándolos sobre escenas arquitectónicas. El Método de Elementos Finitos (MEF) ha sido ampliamente utilizado para análisis térmico. La madurez alcanzada por soluciones de software MEF permite tratar grandes modelos con un alto nivel de detalle y complejidad geométrica. Sin embargo, el cómputo del intercambio radiativo en este contexto implica un desafío computacional, y obliga a empujar los límites de las descripciones físicas conocidas. Algunas técnicas de computación gráfica pueden ser adaptadas a MEF para estimar las cargas solares. En el espectro de radiación térmica, los requisitos de memoria necesarios para almacenar la interacción entre los elementos crecen debido a que todas las superficies urbanas se transforman en fuentes emisoras de radiación. En esta tesis se presenta una metodología basada en MEF para el análisis térmico de escenas urbanas. Un conjunto de técnicas de radiación (para radiación solar y térmica) son desarrolladas e integradas en el software MEF Cast3m. Los algoritmos de radiosidad y ray tracing son utilizados para el cómputo radiativo. Se presentan varios estudios que utilizan diferentes modelos de ciudades. Los resultados obtenidos mediante MEF son comparados con temperaturas medidas por medio de termografías urbanas. Se utilizan técnicas de post-procesamiento para renderizar imágenes térmicas, que permiten concluir que la metodología propuesta produce resultados precisos para los casos analizados. Asimismo, su buen desempeño computacional posibilita realizar este tipo de estudios en computadoras personales

Interactive raytraced caustics

technical reportIn computer graphics, bright patterns of light focused onto matte surfaces are called ?caustics?. We present a method for rendering dynamic scenes with moving caustics at interactive rates. This technique requires some simplifying assumptions about caustic behavior allowing us to consider it a local spatial property which we sample in a pre-processing stage. Storing the caustic locally limits caustic rendering to a simple lookup. We examine a number of ways to represent this data, allowing us to trade between accuracy, storage, run time, and precomputation time

Skeleton based importance sampling for path tracing

International audienceWhen working with large and complex scenes, situations arise where light flux takes complex paths to reach the observer. In such cases, traditional stochastic algorithms, like ray tracing algorithms, will have difficulties to compute noise-free images. Our present research aims to solve this problem using the 3d scene skeleton as a coarse representation. Indeed, curvilinear skeletons can be used to find light paths with higher energy. This article presents our research to use these skeletons for any ray tracing algorithm, allowing a knowledge-based choice when choosing light paths. Our method adds little computation time while producing a more accurate image

A custom designed density estimation method for light transport

We present a new Monte Carlo method for solving the global illumination problem in environments with general geometry descriptions and light emission and scattering properties. Current Monte Carlo global illumination algorithms are based on generic density estimation techniques that do not take into account any knowledge about the nature of the data points --- light and potential particle hit points --- from which a global illumination solution is to be reconstructed. We propose a novel estimator, especially designed for solving linear integral equations such as the rendering equation. The resulting single-pass global illumination algorithm promises to combine the flexibility and robustness of bi-directional path tracing with the efficiency of algorithms such as photon mapping

Human-centric light sensing and estimation from RGBD images: The invisible light switch

Lighting design in indoor environments is of primary importance for at least two reasons: 1) people should perceive an adequate light; 2) an effective lighting design means consistent energy saving. We present the Invisible Light Switch (ILS) to address both aspects. ILS dynamically adjusts the room illumination level to save energy while maintaining constant the light level perception of the users. So the energy saving is invisible to them. Our proposed ILS leverages a radiosity model to estimate the light level which is perceived by a person within an indoor environment, taking into account the person position and her/his viewing frustum (head pose). ILS may therefore dim those luminaires, which are not seen by the user, resulting in an effective energy saving, especially in large open offices (where light may otherwise be ON everywhere for a single person). To quantify the system performance, we have collected a new dataset where people wear luxmeter devices while working in office rooms. The luxmeters measure the amount of light (in Lux) reaching the people gaze, which we consider a proxy to their illumination level perception. Our initial results are promising: in a room with 8 LED luminaires, the energy consumption in a day may be reduced from 18585 to 6206 watts with ILS (currently needing 1560 watts for operations). While doing so, the drop in perceived lighting decreases by just 200 lux, a value considered negligible when the original illumination level is above 1200 lux, as is normally the case in offices

Human-centric light sensing and estimation from RGBD images: the invisible light switch

Lighting design in indoor environments is of primary importance for at least two reasons: 1) people should perceive an adequate light; 2) an effective lighting design means consistent energy saving. We present the Invisible Light Switch (ILS) to address both aspects. ILS dynamically adjusts the room illumination level to save energy while maintaining constant the light level perception of the users. So the energy saving is invisible to them. Our proposed ILS leverages a radiosity model to estimate the light level which is perceived by a person within an indoor environment, taking into account the person position and her/his viewing frustum (head pose). ILS may therefore dim those luminaires, which are not seen by the user, resulting in an effective energy saving, especially in large open offices (where light may otherwise be ON everywhere for a single person). To quantify the system performance, we have collected a new dataset where people wear luxmeter devices while working in office rooms. The luxmeters measure the amount of light (in Lux) reaching the people gaze, which we consider a proxy to their illumination level perception. Our initial results are promising: in a room with 8 LED luminaires, the energy consumption in a day may be reduced from 18585 to 6206 watts with ILS (currently needing 1560 watts for operations). While doing so, the drop in perceived lighting decreases by just 200 lux, a value considered negligible when the original illumination level is above 1200 lux, as is normally the case in offices