Contribution to conference  Open Access

Automatic 3D Reconstruction of Structured Indoor Environments

Pintore G., Mura C., Ganovelli F., Fuentes-perez L., Pajarola R., Gobbetti E.

Department of Informatics  3D reconstruction  knowledge & systems  Indoor scanning  visual computing  Structured reconstruction  Indoor reconstruction  000 Computer science 

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.

Source: SIGGRAPH '20 - ACM SIGGRAPH 2020 Courses, Online Conference, August 24-28, 2020

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Projects (via OpenAIRE)

Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication

ENergy aware BIM Cloud Platform in a COst-effective Building REnovation Context

BibTeX entry
	title = {Automatic 3D Reconstruction of Structured Indoor Environments},
	author = {Pintore G. and Mura C. and Ganovelli F. and Fuentes-perez L. and Pajarola R. and Gobbetti E.},
	doi = {10.1145/3388769.3407469 and 10.5167/uzh-190473},
	booktitle = {SIGGRAPH '20 - ACM SIGGRAPH 2020 Courses, Online Conference, August 24-28, 2020},
	year = {2020}