| Issue |
2012
|
|
|---|---|---|
| Article Number | 02009 | |
| Number of page(s) | 10 | |
| Section | Contribution Full-Papers | |
| DOI | https://doi.org/10.1051/3u3d/201202009 | |
| Published online | 24 October 2012 | |
A generalized approach for historical mock-up acquisition and data modelling: Towards historically enriched 3D city models
1 Musée d’histoire de Nantes - Château des ducs de Bretagne, Nantes, France
2 LUNAM Université, École Centrale Nantes, IRCCYN UMR CNRS 6597, Nantes, France
3 Geomatics Unit, Department of Geography, University of Liège, Belgium
4 LUNAM Université, École Centrale Nantes, CERMA UMR CNRS 1563, Nantes, France
5 CARE Réseau des bibliothèques, University of Liège, Belgium
6 LUNAM Université, Centre François Viète, Université de Nantes, France
Museums are filled with hidden secrets. One of those secrets lies behind historical mock-ups whose signification goes far behind a simple representation of a city. We face the challenge of designing, storing and showing knowledge related to these mock-ups in order to explain their historical value. Over the last few years, several mock-up digitalisation projects have been realised. Two of them, Nantes 1900 and Virtual Leodium, propose innovative approaches that present a lot of similarities. This paper presents a framework to go one step further by analysing their data modelling processes and extracting what could be a generalized approach to build a numerical mock-up and the knowledge database associated. Geometry modelling and knowledge modelling influence each other and are conducted in a parallel process. Our generalized approach describes a global overview of what can be a data modelling process. Our next goal is obviously to apply this global approach on other historical mock-up, but we also think about applying it to other 3D objects that need to embed semantic data, and approaching historically enriched 3D city models.
© Owned by the authors, published by EDP Sciences, 2012
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.