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Precise and dense AI-based mobile 3D reconstruction of indoor scenes by camera-lidar fusion and odometry

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Abstract

We propose a mobile 3D reconstruction method for improving the precision and density of point clouds. It is suitable for hand-held scanners comprised of a colour camera and a lidar. We fuse time-synchronized and spatially registered images and lidar sweeps using deep learning techniques into dense scans, which are then used for progressive reconstruction in an odometry-like manner. We build a prototypic scanner and test our method in an indoor case-study. The results show that our pipeline outperforms reconstructions by other devices and methods, yielding relatively denser and detail-preserving point clouds with a 46% reduction in noise of reconstructed planar surfaces.

Description

Keywords

4013 Geomatic Engineering, 46 Information and Computing Sciences, 40 Engineering

Journal Title

Proceedings of the 2022 European Conference on Computing in Construction

Conference Name

2022 European Conference on Computing in Construction

Journal ISSN

2684-1150

Volume Title

Publisher

University of Turin
Sponsorship
EPSRC (EP/V056441/1)