Comparing Machine and Deep Learning Methods for Large 3D Heritage Semantic Segmentation

• Published in: ISPRS international journal of geo-information Vol. 9; no. 9; p. 535
• Main Authors: Matrone, Francesca, Grilli, Eleonora, Martini, Massimo, Paolanti, Marina, Pierdicca, Roberto, Remondino, Fabio
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2020
• Subjects: Algorithms; Annotations; Architectural elements; Architecture; Artificial intelligence; Case studies; Classification; computer vision; Cultural heritage; Cultural resources; data collection; Datasets; Deep learning; digital cultural heritage; digital images; Historic sites; image analysis; Image segmentation; Lasers; Learning algorithms; lidar; Machine learning; Masonry; Methods; Photogrammetry; point clouds; Semantic segmentation; Semantics; Three dimensional models; Italy

In recent years semantic segmentation of 3D point clouds has been an argument that involves different fields of application. Cultural heritage scenarios have become the subject of this study mainly thanks to the development of photogrammetry and laser scanning techniques. Classification algorithms b...