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Classification Schemes for Visualization of Uncertainty in Digital Hypothetical Reconstruction

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3D Research Challenges in Cultural Heritage II

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10025))

Abstract

The chapter presents the methodology that has been adopted to develop a process for acquiring knowledge that is able to note and make the analysis of preliminary data and interpretation criteria used through a 3D modeling reconstructive process understandable. The classification schemes and criteria adopted aimed to validate the entire process, giving us the ability to visually assess the proper level of knowledge related to the reconstructive process, with its flaws and lacunae, and to carry out comparative operations on the set of data and information held.

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Acknowledgments

I want to express my thanks to Marco Gaiani for his long last and profitable 3D digital reconstruction carried out on the work of Palladio, to Guido Beltramini for the valuable assignment of Palladio’s ‘Project for a twin’ to villa Contarini and to Giacomo Fabbi for the digital reconstruction of ‘Project for a twin’ after the drawing stored up at RIBA, London.

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Authors and Affiliations

  1. Department of Architecture, Alma Mater Studiorum - University of Bologna, viale Risorgimento, 2, Bologna, Italy

    Fabrizio I. Apollonio

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  1. Fabrizio I. Apollonio
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Correspondence to Fabrizio I. Apollonio .

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Editors and Affiliations

  1. TU Dresden , Dresden, Germany

    Sander Münster

  2. TU Darmstadt , Darmstadt, Germany

    Mieke Pfarr-Harfst

  3. Herder Institute for Historical Research on East Central Europe, Marburg, Germany

    Piotr Kuroczyński

  4. Cyprus University of Technology , Limassol, Cyprus

    Marinos Ioannides

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Apollonio, F.I. (2016). Classification Schemes for Visualization of Uncertainty in Digital Hypothetical Reconstruction. In: Münster, S., Pfarr-Harfst, M., Kuroczyński, P., Ioannides, M. (eds) 3D Research Challenges in Cultural Heritage II. Lecture Notes in Computer Science(), vol 10025. Springer, Cham. https://doi.org/10.1007/978-3-319-47647-6_9

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