5D Modelling: An Efficient Approach for Creating Spatiotemporal Predictive 3D Maps of Large-Scale Cultural Resources

Abstract

ABSTRACT:Outdoor large-scale cultural sites are mostly sensitive to environmental, natural and human made factors, implying an imminent need for a spatio-temporal assessment to identify regions of potential cultural interest (material degradation, structuring, conservation). On the other hand, in Cultural Heritage research quite different actors are involved (archaeologists, curators, conservators, simple users) each of diverse needs. All these statements advocate that a 5D modelling (3D geometry plus time plus levels of details) is ideally required for preservation and assessment of outdoor large scale cultural sites, which is currently implemented as a simple aggregation of 3D digital models at different time and levels of details. The main bottleneck of such an approach is its complexity, making 5D modelling impossible to be validated in real life conditions. In this paper, a cost effective and affordable framework for 5D modelling is proposed based on a spatial-temporal dependent aggregation of 3D digital models, by incorporating a predictive assessment procedure to indicate which regions (surfaces) of an object should be reconstructed at higher levels of details at next time instances and which at lower ones. In this way, dynamic change history maps are created, indicating spatial probabilities of regions needed further 3D modelling at forthcoming instances. Using these maps, predictive assessment can be made, that is, to localize surfaces within the objects where a high accuracy reconstruction process needs to be activated at the forthcoming time instances. The proposed 5D Digital Cultural Heritage Model (5D-DCHM) is implemented using open interoperable standards based on the CityGML framework, which also allows the description of additional semantic metadata information. Visualization aspects are also supported to allow easy manipulation, interaction and representation of the 5D-DCHM geometry and the respective semantic information. The open source 3DCityDB incorporating a PostgreSQL geo-database is used to manage and manipulate 3D data and their semantics.

Virtual reality exposure for OCD: Is it feasible? [Exposición mediante realidad virtual para el TOC: ¿Es factible?]

“…Therefore, each of them will be accessible through the semantic context information added to the virtual reproduction. This way, the data will be directly linked to the element or part of the research object it holds information about (Dell' Unto et al 2016;Doulamis et al 2015;Koehl et al 2008;Landeschi et al 2015;Manferdini et al 2008;Wulff and Koch 2013). Therefore, if the coordinates are known, the data will be inserted in the same location than in real life.…”

“…However, a 3D model provides a static view of a recorded monument, site or object (De Roo et al 2013a;De Roo et al 2013b). Within the 4D AIS, the researcher should therefore be able to assign a time frame to each element (Belussi et al 2015;Doulamis et al 2015;Manferdini et al 2008). Once this step is done, he could then choose which sections should be visible by applying a terminus post quem and a terminus ante quem.…”

“…A timeline feature is also being considered. This tool will be able to display chronologically the appearance and, in some cases, the disappearance of the timed parts (Doulamis et al 2015;Hallot et al 2015;Van Ruymbeke et al 2015).…”

“…For this concept to be effective, the semantic classification of the point cloud will be crucial. Indeed, it will be very important to sort the data correctly and to link it to the appropriate sections of the 3D model (Doulamis et al 2015;Wulff and Koch 2013). The attributes that will be added to them will also need to be carefully selected so that the information, if it is linked to two or more parts, is still available even if some of those sections are not on display.…”

“…Three-dimensional recording of cultural heritage acquires a great importance since it assists in preserving monuments and objects that are likely to face natural disasters, wars or degradation over time (Doulamis et al 2015;Entwistle et al 2009). …”