GRAVITATE: Geometric and semantic matching for cultural
heritage artefacts
GRAVITATE: Geometric and semantic matching for cultural
heritage artefacts
The GRAVITATE project is developing techniques that bring together geometric and semantic data analysis to provide a new and more effective method of re-associating, reassembling or reunifying cultural objects that have been broken or dispersed over time. The project is driven by the needs of archaeological institutes, and the techniques are exemplified by their application to a collection of several hundred 3D-scanned fragments of large-scale terracotta statues from Salamis, Cyprus. The integration of geometrical feature extraction and matching with semantic annotation and matching into a single decision support platform will lead to more accurate reconstructions of artefacts and greater insights into history. In this paper we describe the project and its objectives, then we describe the progress made to date towards achieving those objectives: describing the datasets, requirements and analysing the state of the art. We follow this with an overview of the architecture of the integrated decision support platform and the first realisation of the user dashboard. The paper concludes with a description of the continuing work being undertaken to deliver a workable system to cultural heritage curators and researchers.
199-202
Association for Computing Machinery
Phillips, Stephen
47610c30-a543-4bac-a96a-bc1fce564a59
Walland, Paul
ee411ac1-9ebc-4513-a691-a3b95b599d7f
Modafferi, Stefano
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Spagnuolo, Michela
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Catalano, Chiara Eva
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Oldman, Dominic
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Tal, Ayellet
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Shimshoni, Illan
4402eb91-a481-4887-a064-03b449144573
Hermon, Sorin
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November 2016
Phillips, Stephen
47610c30-a543-4bac-a96a-bc1fce564a59
Walland, Paul
ee411ac1-9ebc-4513-a691-a3b95b599d7f
Modafferi, Stefano
2f15a6fa-a4c3-4f43-998f-df7d88f08a78
Spagnuolo, Michela
919cd0b4-55a3-4122-83f6-070159550382
Catalano, Chiara Eva
d21e7b60-1f87-4cdb-8007-218d46284d4b
Oldman, Dominic
1e143b97-6d17-4020-bf96-352392d3410a
Tal, Ayellet
03b196d1-8e53-40cf-8771-9bd792fa40d7
Shimshoni, Illan
4402eb91-a481-4887-a064-03b449144573
Hermon, Sorin
a5f5bb6e-3325-4bc0-8517-7f5fa8c4712a
Phillips, Stephen, Walland, Paul, Modafferi, Stefano, Spagnuolo, Michela, Catalano, Chiara Eva, Oldman, Dominic, Tal, Ayellet, Shimshoni, Illan and Hermon, Sorin
(2016)
GRAVITATE: Geometric and semantic matching for cultural
heritage artefacts.
In GCH '16 Proceedings of the 14th Eurographics Workshop on Graphics and Cultural Heritage.
Association for Computing Machinery.
.
(doi:10.2312/gch.20161407).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The GRAVITATE project is developing techniques that bring together geometric and semantic data analysis to provide a new and more effective method of re-associating, reassembling or reunifying cultural objects that have been broken or dispersed over time. The project is driven by the needs of archaeological institutes, and the techniques are exemplified by their application to a collection of several hundred 3D-scanned fragments of large-scale terracotta statues from Salamis, Cyprus. The integration of geometrical feature extraction and matching with semantic annotation and matching into a single decision support platform will lead to more accurate reconstructions of artefacts and greater insights into history. In this paper we describe the project and its objectives, then we describe the progress made to date towards achieving those objectives: describing the datasets, requirements and analysing the state of the art. We follow this with an overview of the architecture of the integrated decision support platform and the first realisation of the user dashboard. The paper concludes with a description of the continuing work being undertaken to deliver a workable system to cultural heritage curators and researchers.
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Accepted/In Press date: 11 July 2016
e-pub ahead of print date: 5 October 2016
Published date: November 2016
Venue - Dates:
Eurographics Workshop on Graphics and Cultural Heritage (GCH 2016), Genova, Italy, 2016-10-05 - 2016-10-07
Organisations:
IT Innovation
Identifiers
Local EPrints ID: 402427
URI: http://eprints.soton.ac.uk/id/eprint/402427
PURE UUID: b8bf51d4-591c-4ea4-b77c-706fa9519c10
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Date deposited: 09 Nov 2016 09:59
Last modified: 16 Mar 2024 04:10
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Contributors
Author:
Stephen Phillips
Author:
Paul Walland
Author:
Stefano Modafferi
Author:
Michela Spagnuolo
Author:
Chiara Eva Catalano
Author:
Dominic Oldman
Author:
Ayellet Tal
Author:
Illan Shimshoni
Author:
Sorin Hermon
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