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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Saving Cultural Heritage with Digital Make-Believe: Machine Learning and Digital Techniques to the Rescue

Yasser, A, M, Clawson, Kathy, Bowerman, Chris and Lévêque, M (2017) Saving Cultural Heritage with Digital Make-Believe: Machine Learning and Digital Techniques to the Rescue. HCI '17: Proceedings of the 31st British Computer Society Human Computer Interaction Conference (97). pp. 1-5.

Item Type: Article

Abstract

The application of digital methods for content-based curation and dissemination of cultural heritage data offers unique advantages for physical sites at risk of damage. In areas affected by 2011 Arab spring, digital may be the only approach to create believable cultural experiences. We propose a framework incorporating computational methods such as: digital image processing, multi-lingual text analysis, and 3D modelling, to facilitate enhanced data archive, federated search, and analysis. Potential use cases include experiential search, damage assessment, virtual site reconstruction, and provision of augmented information for education and cultural preservation. This paper presents initial findings from an empirical evaluation of existing scene classification methods, applied to detection of cultural heritage sites in the Palmyra region. Results indicate that deep learning offers an appropriate solution to semantic annotation of publicly available cultural heritage image data.

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More Information

Additional Information: British Human Computer Interaction Conference; Sunderland University, St Peter's Campus; 3 - 6 Jul 2017
Depositing User: Kathy Clawson

Identifiers

Item ID: 7634
Identification Number: https://doi.org/10.14236/ewic/HCI2017.97
URI: http://sure.sunderland.ac.uk/id/eprint/7634
Official URL: https://dl.acm.org/doi/10.14236/ewic/HCI2017.97

Users with ORCIDS

ORCID for Kathy Clawson: ORCID iD orcid.org/0000-0001-8431-1524

Catalogue record

Date Deposited: 03 Aug 2017 08:35
Last Modified: 15 Dec 2020 14:00

Contributors

Author: Kathy Clawson ORCID iD
Author: A, M Yasser
Author: Chris Bowerman
Author: M Lévêque

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Computing > Artificial Intelligence
Computing > Human-Computer Interaction
Computing

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