High-fidelity rendering and display of cultural heritage

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Abstract

Many Cultural Heritage (CH) reconstructions today use black box rendering
solutions with little regard to appropriate addition of lighting, material light
reflectance properties or light transport algorithms. This may be in favour of
faster computational performance or is simply not a priority (as long as the end
result is visually convincing). This can lead to misrepresenting CH environments,
both in their present and past forms. The handful of publications that do pay
special attention to lighting, emphasise on case specific problems rather than
attempting to generalise a rendering pipeline tailored to the needs of CH scenes.
The dissertation presents a research framework to render CH scenes appropriately
and novel approaches to document, estimate and accelerate global illumination
for virtual archaeology purposes. First, three reconstruction case
studies with an unbiased rendering pipeline in mind are presented. Second, a research
framework to reverse-engineer the past (through high-fidelity rendering) is
overviewed. Through this proposed framework, it is possible to create historically
and physically accurate models based on input available today. The approach is
an extension to the established Predictive Rendering pipeline by introducing a
historical comparison component. Third, a novel method to preview appropriately
lit virtual environments is presented. The method is particularly useful for
CH rendition, extending Image-based Lighting to employ empirically captured
illumination to relight interior CH scenes. It is intended as a fast high-quality
preview method for CH models before a high-quality render is initiated, therefore
also making it useful in a Predictive Rendering context. Finally, a study on uses
of High Dynamic Range (HDR) Imaging specifically for CH documentation and
display purposes is also presented. This includes the use of a novel prototype
camera to illustrate a proof-of-concept on how to document vast dynamic ranges
of light based on the needs of CH research using HDR video.

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