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


      1 , 2 , 1 , 1

      Electronic Visualisation and the Arts (EVA 2017) (EVA)

      Electronic Visualisation and the Arts

      11 – 13 July 2017

      Semantic Archive, Image Retrieval, Cultural Heritage, Data Mining, Deep Learning



            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.


            Author and article information

            July 2017
            July 2017
            : 1-5
            [ 1 ]Faculty of Computer Science, University of Sunderland, Sunderland, SR1 3SD, UK
            [ 2 ]Physics Department, Faculty of Science at Qena, South Valley University, 83523, Egypt
            © Yasser et al. Published by BCS Learning and Development. Proceedings of British HCI 2017 – Digital Make-Believe, Sunderland, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Electronic Visualisation and the Arts (EVA 2017)
            London, UK
            11 – 13 July 2017
            Electronic Workshops in Computing (eWiC)
            Electronic Visualisation and the Arts
            Product Information: 1477-9358BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Electronic Workshops in Computing


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