Figures & data
Figure 1. Piazza dei Miracoli, Pisa: main monuments and location of the study area.
Figure 2. Overall workflow of the proposed approach.
Figure 3. Model segmentation for the ortho-mosaic generation.
Figure 4. Steps of the proposed methodological approach, involving: i) thematic mapping over the orthophoto; ii) projection of annotations on the mesh representation; iii) point-based representation and iv) point-based thematic mapping over the 3D model.
Figure 5. Ortho-photo (planar projection): original and corrected colour.
Figure 6. Orthophoto (cylindrical projection): original and corrected colour.
Figure 7. Example of thematic mapping of digital orthophotos: i) material survey; ii) state of degradation; iii) intervention strategies.
Figure 8. Example of annotations of the material ‘white marble’, performed via McNeel Rhinoceros.
Figure 9. Example of annotations of the material ‘white marble’ in the upper part of the transept, performed via McNeel Rhinoceros.
Figure 10. 2D/3D transfer of semantic annotations in the form of closed polylines or curves. Planar projection.
Figure 11. Cylindrical projection.
Figure 12. The mesh before (i) and after (ii) the uniform resampling procedure.
Figure 13. Mesh resampling of the overall model.
Figure 14. Identification of Surface Information Points.
Figure 15. Algorithm for the transfer of semantic annotations in McNeel Rhinoceros visual programming interface.
Figure 16. Point-based annotation of the ‘encrustation’ phenomenon.
Figure 17. 2D/3D information propagation.
Figure 18. Comparison between SIPs detected via manual (a) and automatic (b) annotations, respectively.
Figure 19. Semantic segmentation of the model with identification of classes of typological elements. Future work will consider the model resampling based on these primitive architectural components.
