New Frontiers of Image-Based Surveying

Maurizio Perticarini
Additional contact information
Maurizio Perticarini: University of Padua, DICEA

Chapter Chapter 3 in Machine Learning and Mixed Reality for the Enhancement of Cultural Heritage, 2024, pp 53-59 from Springer

Abstract: Abstract The development of Nvidia RTX GPUs and neural networks, such as Neural Radiance Field (NeRF), has revolutionized 3D graphics. These technologies enhance realism and rendering efficiency. NeRF generates 3D views from 2D images, reducing computation times and replacing GAN networks. Nvidia’s Instant NeRF algorithm uses multi-resolution hash grid encoding to speed up rendering, allowing detailed scenes to be created from a few photos. Applications include the reconstruction of moving objects and the surveying of inaccessible artworks, opening new frontiers in spatial representation.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-71287-6_3

Ordering information: This item can be ordered from
http://www.springer.com/9783031712876

DOI: 10.1007/978-3-031-71287-6_3

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().