ARCHITECTURAL HERITAGE RECOGNITION IN HISTORICAL FILM FOOTAGE USING NEURAL NETWORKS
Francesca Condorelli|Fulvio Rinaudo|Francesco Salvadore|Stefano Tagliaventi
Abstract. Researching historical archives for material suitable photogrammetry is essential the documentation and 3D reconstruction of Cultural Heritage, especially when this heritage has been lost or transformed over time. This research presents an innovative workflow which combines photogrammetric procedure with Machine Learning processing film footage. A Neural Network trained to automatically detect frames in architectural appears. These are subsequently processed using finally resulting model assessed metric quality. paper proposes best practises training validation on a Heritage asset. The algorithm was tested through case study Tour Saint Jacques Paris entirely new dataset created. findings encouraging both terms saving human effort improvement survey pipeline. tool can help researchers better manage organize information.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences|DOAJ (DOAJ: Directory of Open Access Journals)