Cultural Heritage Predictive Rendering

  • Authors:

  • Jassim Happa;Tom Bashford-Rogers;Alexander Wilkie;Alessandro Artusi;Kurt Debattista;Alan Chalmers

  • Affiliations:

  • International Digital Laboratory, University of Warwick, UK;International Digital Laboratory, University of Warwick, UK;Charles University in Prague, Czech Republic;CASToRC Cyprus Institute, Cyprus andUniversity of Girona UdG, Spain j.happa@warwick.ac.uk;International Digital Laboratory, University of Warwick, UK;International Digital Laboratory, University of Warwick, UK

  • Venue:
  • Computer Graphics Forum
  • Year:
  • 2012

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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. © 2012 Wiley Periodicals, Inc. (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).)