AUTOMATIC STRUCTURING OF PHOTOGRAPHIC COLLECTIONS FOR SPATIO-TEMPORAL MONITORING OF RESTORATION SITES: PROBLEM STATEMENT AND CHALLENGES
- 1CY Cergy Paris Université, ENSEA, CNRS, ETIS, F-95000 Cergy, France
- 2MAP, UMR 3495, CNRS/MC, Marseille, France
- 3LASTIG, Univ. Gustave Eiffel, IGN-ENSG, 94160 Saint-Mande, France
Keywords: heritage science, computer vision, content-based retrieval, similarity metrics, multimodal data analytics, data semantics
Abstract. Over the last decade, a large number of digital documentation projects have demonstrated the potential of image-based modelling of heritage objects in the context of documentation, conservation, and restoration. The inclusion of these emerging methods in the daily monitoring of the activities of a heritage restoration site (context in which hundreds of photographs per day can be acquired by multiple actors, in accordance with several observation and analysis needs) raises new questions at the intersection of big data management, analysis, semantic enrichment, and more generally automatic structuring of this data. In this article we propose a data model developed around these questions and identify the main challenges to overcome the problem of structuring massive collections of photographs through a review of the available literature on similarity metrics used to organise the pictures based on their content or metadata. This work is realized in the context of the restoration site of the Notre-Dame de Paris cathedral that will be used as the main case study.