Physically-based rendering in Computer Graphics requires the knowledge of material properties other than 3D shapes, textures and colors, in order to solve the rendering equation. A number of material models have been developed, since no model is currently able to reproduce the full range of available materials. Although only few material models have been widely adopted in current rendering systems, the lack of standardisation causes several issues in the 3D modelling workflow, leading to a heavy tool dependency of material appearance. In industry, final decisions about products are often based on a virtual prototype, a crucial step for the production pipeline, usually developed by a collaborations among several departments, which exchange data. Unfortunately, exchanged data often tends to differ from the original, when imported into a different application. As a result, delivering consistent visual results requires time, labour and computational cost. This thesis begins with an examination of the current state of the art in material appearance representation and capture, in order to identify a suitable strategy to tackle material appearance consistency. Automatic solutions to this problem are suggested in this work, accounting for the constraints of real-world scenarios, where the only available information is a reference rendering and the renderer used to obtain it, with no access to the implementation of the shaders. In particular, two image-based frameworks are proposed, working under these constraints. The first one, validated by means of perceptual studies, is aimed to the remapping of BRDF parameters and useful when the parameters used for the reference rendering are available. The second one provides consistent material appearance across different renderers, even when the parameters used for the reference are unknown. It allows the selection of an arbitrary reference rendering tool, and manipulates the output of other renderers in order to be consistent with the reference.

Ray tracing is a popular technique used in movies and video games to create compelling visuals. Ray traced computer images are increasingly becoming more realistic and almost indistinguishable from real-word images. Due to the complexity of scenes and the desire for high resolution images, ray tracing can become very expensive in terms of computation and memory. To address these concerns, researchers have examined data structures to efficiently store geometric and material information. Sparse voxel octrees (SVOs) and directed acyclic graphs (DAGs) have proven to be successful geometric data structures for reducing memory requirements. Moxel DAGs connect material properties to these geometric data structures, but experience limitations related to memory, build times, and render times. This thesis examines the efficacy of connecting an alternative material data structure to existing geometric representations. The contributions of this thesis include the creation of a new material representation using hashing to accompany DAGs, a method to calculate surface normals using neighboring voxel data, and a demonstration and validation that DAGs can be used to super sample based on proximity. This thesis also validates the visual acuity from these methods via a user survey comparing different output images. In comparison to the Moxel DAG implementation, this work increases render time, but reduces build times and memory, and improves the visual quality of output images.