Processing historical photographs and film footage with Photogrammetry and Artificial Intelligence for Cultural Heritage documentation and virtual reconstruction



The specific objective of this thesis is to offer an excursion through the metric potentialities of different data  available in historical archives, by considering the essential role of photogrammetry. The aim is to explore how metric information about buildings which no longer exist or transformed over time could be extracted from old photographs and videos of different quality, for their 3D virtual reconstruction analysing the material stored in historical archives to support researchers and experts in historical research of Cultural Heritage.

In order to process these data and to obtain metrically certified results, a modification of the algorithms of the standard photogrammetric pipeline was necessary. This purpose was achieved with the use of open-source Structure-from-Motion algorithms and the creation of a specific benchmark to compare the results.

Besides the processing of historical photograph, photogrammetry is combined with Artificial Intelligence to improve ways to search for architectural heritage in video material and to reduce the effort of manually examining them by the operator in the archive in terms of efficiency and time.


Computer Vision, Motion Tracking, Object Recognition, Machine Learning, Image and Video Processing, Cultural Heritage

Author Biography

Francesca Condorelli, Politecnico di Torino

DAD, Department of Architecture and Design, Politecnico di Torino, 10125 Turin, Italy




Download data is not yet available.