Systems structured to reconstruct the multilevel 3D spatial perception in order to define the density of the objects and their colorimetric properties.
Published in Chapter:
Machine Learning and Artificial Intelligence for Smart Visualization, Presentation, and Study of Architecture and Engineering in the Urban Environment: Visualizing City Progress
Andrea Giordano (University of Padova, Italy), Kristin Love Huffman (Duke University, USA), Rachele Angela Bernardello (University of Padua, Italy), Maurizio Perticarini (Università degli Studi Luigi Vanvitelli, Italy), and Alessandro Basso (University of Camerino, Italy)
Copyright: © 2022
|Pages: 17
DOI: 10.4018/978-1-6684-4854-0.ch009
Abstract
This research experiments the theme of cultural heritage (CH) in architectural/engineering fields, located in urban space. Primary sources and new tactics for digital reconstruction allow interactive contextualization-access to often inaccessible data creating pedagogical apps for spreading. Digital efforts are central, in recent years based on new technological opportunities that emerged from big data, Semantic Web technologies, and exponential growth of data accessible through digital libraries – EUROPEANA. Also, the use of data-based BIM allowed the gaining of high-level semantic concepts. Then, interdisciplinary collaborations between ICT and humanities disciplines are crucial for the advance of workflows that allow research on CH to exploit machine learning approaches. This chapter traces the visualizing cities progress, involving Duke and Padua University. This initiative embraces the analysis of urban systems to reveal with diverse methods how documentation/understanding of cultural sites complexities is part of a multimedia process that includes digital visualization of CH.