Processing Historical Film Footage with Photogrammetry and Machine Learning for Cultural Heritage Documentation

Historical film footages in many cases represent the only remaining traces of Cultural Heritage that has been lost or changed over time. Photogrammetry is a powerful technique to document the heritage transformations, but its implementation is technically challenging due to the difficulty in finding the historical data suitable to be process. This paper aims to examine the possibility to extract metric information of historic buildings from historical film footage for their 3D virtual reconstruction. In order to make automatic the research of a specific monument to document, in the first part of the study an algorithm for the detection of architectural heritage in historical film footage was developed using Machine Learning. This algorithm allowed the identification of the frames in which the monument appeared and their processing with photogrammetry. In the second part, with the implementation of open source Structure-from-Motion algorithms, the 3D virtual reconstruction of the monument and its metric information were obtained. The results were compared with a benchmark for evaluate the metric quality of the model, according to specific camera motion. This research, analysing the metric potentialities of historical film footage, provides fundamental support to documentation of Cultural Heritage, creating tools useful for both geomatics and historians.