Cultural Heritage Predictive Rendering

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Date
2012
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Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
High‐fidelity rendering can be used to investigate Cultural Heritage (CH) sites in a scientifically rigorous manner. However, a high degree of realism in the reconstruction of a CH site can be misleading insofar as it can be seen to imply a high degree of certainty about the displayed scene—which is frequently not the case, especially when investigating the past. So far, little effort has gone into adapting and formulating a Predictive Rendering pipeline for CH research applications. In this paper, we first discuss the goals and the workflow of CH reconstructions in general, as well as those of traditional Predictive Rendering. Based on this, we then propose a research framework for CH research, which we refer to as ‘Cultural Heritage Predictive Rendering’ (CHPR). This is an extension to Predictive Rendering that introduces a temporal component and addresses uncertainty that is important for the scene’s historical interpretation. To demonstrate these concepts, two example case studies are detailed.High‐fidelity rendering can be used to investigate Cultural Heritage (CH) sites in a scientifically rigorous manner. However, a high degree of realism in the reconstruction of a CH site can be misleading insofar as it can be seen to imply a high degree of certainty about the displayed scene‐which is frequently not the case, especially when investigating the past. So far, little effort has gone into adapting and formulating a Predictive Rendering pipeline for CH research applications. In this paper, we first discuss the goals and the workflow of CH reconstructions in general, as well as those of traditional Predictive Rendering. Based on this, we then propose a research framework for CH research, which we refer to as ‘Cultural Heritage Predictive Rendering’ (CHPR).
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@article{
10.1111:j.1467-8659.2012.02098.x
, journal = {Computer Graphics Forum}, title = {{
Cultural Heritage Predictive Rendering
}}, author = {
Happa, Jassim
and
Bashford-Rogers, Tom
and
Wilkie, Alexander
and
Artusi, Alessandro
and
Debattista, Kurt
and
Chalmers, Alan
}, year = {
2012
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd.
}, ISSN = {
1467-8659
}, DOI = {
10.1111/j.1467-8659.2012.02098.x
} }
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