| EPSRC Reference: |
EP/J014338/1 |
| Title: |
Laymen To The Help Of Experts: Crowdsourcing To Aid The Reassembly Of Ancient Frescoes |
| Principal Investigator: |
Weyrich, Professor TA |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computer Science |
| Organisation: |
UCL |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
01 July 2012 |
Ends: |
30 September 2014 |
Value (£): |
98,209
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| EPSRC Research Topic Classifications: |
| Computer Graphics & Visual. |
Image & Vision Computing |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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07 Mar 2012
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EPSRC ICT Responsive Mode - Mar 2012
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Announced
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Summary on Grant Application Form |
Reconstruction of fragmented objects is of great interest in archaeology, where artefacts are often found in a fractured state, and the effort of manually putting the broken pieces together represents a significant amount of time and resources. Representative of this problem is our work on documenting and reconstructing fragments of Late-Bronze-Age wall paintings from the site of Akrotiri on the volcanic island of Thera (modern-day Santorini, Greece). As is common in archaeological finds, the wall paintings are excavated as tens of thousands of pieces, and searching for matches is a daunting manual process that dwarfs the available resources.
In a previous project we have contributed methods to acquire object fragments efficiently, identify pairwise matches between fragments, interactively refine automatically suggested matches and automatically assemble them into larger clusters. However, unavoidable error sources in acquisition and processing, but also physical influences, such a erosion and other damage over the last 3,500 years, lead to uncertainty in identifying matches between fragments. We find that humans are required to sift the automated match suggestions and that without massively parallelising and without introducing redundancy in the manual sifting, there will always be a substantial number of matches go unnoticed.
This work proposes a crowdsourcing solution to obtain this goal. We believe that a key novelty lies in the fact that we are trying to let non-expert solve a problem in the digital domain that normally requires experts to operate in the physical domain. We believe that we are excellently positioned to turn this into a high-impact project with generalisable outcomes.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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