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.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:756481 |
| Date | January 2018 |
| Creators | Guarnera, Dar'ya |
| Publisher | Loughborough University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://dspace.lboro.ac.uk/2134/33410 |
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