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Predictive digitisation of cultural heritage objects

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Abstract

3D digitisation has been instrumental in the cultural heritage domain for over a decade, contributing to the digital preservation and dissemination of cultural heritage. Still, the typical 3D acquisition workflow remains complex and time-consuming. This work presents the concept of predictive digitisation by means of a platform, aiming to speed-up and simplify 3D digitisation, exploiting similarities in digital repositories of Cultural Heritage objects.

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Notes

  1. http://hampson.cast.uark.edu.

  2. http://www.presious.eu/.

  3. (http://hampson.cast.uark.edu)

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Acknowledgements

This work was supported by the EC FP7 STREP Project PRESIOUS, grant no. 600533.

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Authors and Affiliations

  1. Democritus University of Thrace, Xanthi, Greece

    Ioannis Pratikakis & Fotis Arnaoutoglou

  2. ATHENA Research and Innovation Center, Xanthi, Greece

    Ioannis Pratikakis & Fotis Arnaoutoglou

  3. Graz University of Technology, Graz, Austria

    Pavlos Mavridis

  4. Athens University of Economics and Business, Athens, Greece

    Michalis A. Savelonas & Georgios Papaioannou

  5. NTNU, Trondheim, Norway

    Konstantinos Sfikas

  6. AICON 3D systems, GmbH, Braunschweig, Germany

    Dirk Rieke-Zapp

Authors
  1. Ioannis Pratikakis
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  2. Michalis A. Savelonas
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  3. Pavlos Mavridis
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  4. Georgios Papaioannou
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  5. Konstantinos Sfikas
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  6. Fotis Arnaoutoglou
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  7. Dirk Rieke-Zapp
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Correspondence to Ioannis Pratikakis.

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Pratikakis, I., Savelonas, M.A., Mavridis, P. et al. Predictive digitisation of cultural heritage objects. Multimed Tools Appl 77, 12991–13021 (2018). https://doi.org/10.1007/s11042-017-4928-y

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  • DOI: https://doi.org/10.1007/s11042-017-4928-y

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