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Laboratoire d'InfoRmatique en Image et Systèmes d'information

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Laboratoire d'InfoRmatique en Image et Systèmes d'information
UMR 5205 CNRS / INSA Lyon / Université Claude Bernard Lyon 1 / Université Lumière Lyon 2 / École Centrale de Lyon
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Vincent Jaillot

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PhD student

Team Geometrical Modeling, Computational Geometry, Procedural Generation
 
Institution Lumière University of Lyon 2
Location Nautibus (Université Lyon1)
 
E-mail vincent.jaillot at liris.cnrs.fr
Contact details Publications Thesis
 
Subject Models, methods and tool to integrate and communicate heterogeneous, multisources and multidimensional data : contributing to cultural heritage making
Abstract Cultural heritage (tangible and intagible) is currently mainly defined by institutions such as UNESCO. Occasionally, some local collectivities or associations also proposes to broaden cultural heritage lists. In order to emphasize citizen's initiatives to contribute to cultural heritage making, the UNESCO has adopted the recommandation on the Historic Urban Landscape (HUL) in 2011. It allows a broaden conception of cultural heritage by going beyond common criterias of its definition and by considering all contributions, whether they are coming from experts or not. In this context, it becomes mandatory to propose models, methods and tools, related to digital urban modelisation and allowing citizen's and associations to share their knowledge about cultural heritage in a participative and collaborative way with the purpose of enhancing numerical urban models. Gathering, managing and communicating this knowledge which can be defined as heterogeneous data (different types and natures), coming from different sources and having multiple dimensions (spatial, temporal, thematic, etc.) will lead us to address several scientific problems. First, we will have to propose models for this data and processes allowing navigation in it. We will also have to work on the projection of this data in 4D (spatial and temporal) and on their visualisation in a virtual urban environment. Finally, we will have to study the quality of this data and ways to visualise it as this data can come from experts or not and, most of the time, only contains partial information.
Advisor Gilles Gesquiere
Advisor Sylvie Servigne

Last update : 2017-06-30 10:22:17