Please use this identifier to cite or link to this item: https://dspace.crs4.it/jspui/handle/1138/13
Title: Automatic 3D Reconstruction of Structured Indoor Environments
Authors: Pintore, Giovanni 
Mura, Claudio 
Ganovelli, Fabio 
Fuentes-Perez, Lizeth 
Pajarola, Renato 
Gobbetti, Enrico 
Affiliations: CRS4 
University of Zurich 
ISTI-CNR 
University of Zurich 
University of Zurich 
CRS4 
Keywords: visual computing;3D reconstruction;indoor reconstruction;indoor scanning;structured reconstruction
Issue Date: 2020
Publisher: ACM
Project: Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication 
ENergy aware BIM Cloud Platform in a COst-effective Building REnovation Context 
AMAC 
TDM 
VIGECLAB 
Related Publication(s): SIGGRAPH 2020 Courses
Start page: 10:1
End page: 10:218
Conference: SIGGRAPH 
Abstract: 
Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need to cope with noisy and partial captured data, many open research problems remain, despite the substantial progress made in the past decade. In this tutorial, we provide an up-to-date integrative view of the field, bridging complementary views coming from computer graphics and computer vision. After providing a characterization of input sources, we define the structure of output models and the priors exploited to bridge the gap between imperfect sources and desired output. We then identify and discuss the main components of a structured reconstruction pipeline, and review how they are combined in scalable solutions working at the building level. We finally point out relevant research issues and analyze research trends.
Description: 
Tutorial notes
URI: https://dspace.crs4.it/jspui/handle/1138/13
DOI: 10.1145/3388769.3407469
Appears in Collections:CRS4 publications

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