Open AccessTOWARDS AN INTEGRATED DESIGN METHODOLOGY FOR H-BIM
Author(s) -
E. Pellis,
Andrea Masiero,
Grazia Tucci,
Michele Betti,
Pierre Grussenmeyer
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.4995/arqueologica9.2021.12158
Subject(s) - computer science , building information modeling , point cloud , segmentation , cultural heritage , point (geometry) , data science , deep learning , cloud computing , artificial intelligence , engineering , geometry , mathematics , archaeology , compatibility (geochemistry) , chemical engineering , history , operating system
In recent years, the numerous advantages introduced by Building Information modelling (BIM) have led in its application on the heritage environment and giving birth to the concept of H-BIM (Heritage BIM). The resulting demand in heritage survey data processing has focused this research on the development of strategies and methods to improve the construction of three-dimensional and informative models starting from 3D point clouds. The implementation of an automated procedure is fundamental for easing and speeding up the survey data processing and one of the most challenging tasks to achieve this purpose is the problem of semantic segmentation. The research presented in this paper aims at testing already existing methods and exploring new strategies for 3D point cloud semantic segmentation on heritage scenarios focusing on deep learning and neural network techniques.