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PRESIOUS

Financiado

Cerrado

PREdictive digitization reStoration and degradatIOn assessment of cultUral heri...

PREdictive digitization reStoration and degradatIOn assessment of cultUral heritage objectS Europe must proactively exploit markets in which it has strategic advantages in order to develop products that will make it a leading player. One such area is Cultural Heritage (CH). Having studied the needs of CH for a number of... ver más

31/01/2016

SINTEF

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 6 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2016-01-31 No tenemos la información de la convocatoria

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Información adicional privada

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6 Participantes

SINTEF

0.00€ | Lider

HEXAGON DEU01 GMBH

N.D. | Participante

UKON

N.D. | Participante

National Gallery of Athens -...

N.D. | Participante

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Líder del proyecto

SINTEF AS No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Europe must proactively exploit markets in which it has strategic advantages in order to develop products that will make it a leading player. One such area is Cultural Heritage (CH). Having studied the needs of CH for a number of years, the project team is now in a position to propose breakthrough ICT solutions to the identified challenges: a) the difficulty and inefficiency of the 3D digitisation process, b) the quantification of stone monument degradation, and c) the reconstruction of objects from large numbers of constituent fragments that may be worn, immovable, dispersed or incomplete.<br/>Using a common core of geometric processing, analysis and retrieval methods, PRESIOUS aims at predictive geometric augmentation technology with the following scientific objectives:a) On-the-fly auto-completion for 3D digitization that exploits similar template models to allow gradual shape prediction from partially digitized objects. Such a breakthrough system opens a whole new range of possibilities for decreased acquisition times and simplified procedures, leading to an order of magnitude reduction in effort and cost. This technology is a prime candidate for exploitation by our industrial partner.b) Estimation and prediction of monument degradation. The project will investigate models for forward and inverse erosion prediction based on targeted high-accuracy surface scans, allowing one to essentially move the artefact's surface condition "back and forth in time" and visualize and measure the dynamic state of the deteriorating object. This tool is also likely to be applicable in areas outside CH, such as civil engineering.c) 3D CH object repair. Automated, predictive reconstruction from fragmented CH objects that goes beyond reassembly by proposing the synthesis of missing parts using geometry auto-completion. This will aid the physical and virtual restoration process.

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