Realistic Image Synthesis with Light Transport

Abstract:

In interior and lighting design, 3D animation, and computer games, it is always demanded to produce visually pleasant content to users and audience. A key to achieve this goal is to render scenes in a physically correct manner and account for all types of light transport in the scenes, including direct and indirect illumination. Rendering from given scene data can be regarded as forward light transport.

In augmented reality, it is often required to render a scene that has real and virtual objects placed together. The real scene is often captured and scene information is extracted to provide input to rendering. For this task, light transport matrix can be used. Inverse light transport is the process of extracting scene information from a light transport matrix, e.g., geometry and materials. Understanding both forward and inverse light transport are important to produce realistic final images.

This thesis is a two-part study about light transport. The first part is dedicated to global illumination and many-light rendering. First, a new importance sampling technique which is built upon the Metropolis algorithm that utilizes virtual lights in many-light rendering as incoming radiance distribution is presented. Second, an approach to compensate and reduce artifacts in many-light rendering is proposed. Our experiments show that our techniques can improve the effectiveness in many-light rendering by reducing noise and visual artifacts.

The second part of the thesis is a study about inverse light transport. First, an extension to compressive dual photography is presented to accelerate the demultiplexing of dual images, which is useful for preview for light transport capturing. Second, a new formulation to acquire geometry from radiometric data such as interreflections is presented. Our experiments with synthetic data show that depth and surface orientation can be reconstructed by solving a system of polynomials.