Back to Search Start Over

Datasets of captured images of three different devices for photogrammetry calculation comparison and integration into a laserscan point cloud of a built environment

Authors :
René Hellmuth
Florian Wehner
Alexandros Giannakidis
Publica
Source :
Data in Brief, Data in Brief, Vol 33, Iss, Pp 106321-(2020)
Publication Year :
2020

Abstract

The presented data article aims to provide the whole dataset obtained during an experiment of updating laser scan point clouds with photogrammetry meshes. In this context, the data quality and calculation time of photogrammetry models from different recording devices and different software solutions were compared. It was investigated whether photos from smartphones are also appropriate for updating point clouds by using photogrammetry in a factory environment. The photos of a technical installation were taken in 08:30 min with these three devices: Nikon D810 with Sigma art 24 mm, iPhone 6 and iPhone XS. With each of the mentioned devices, three datasets have been created to provide enough data for the comparisons. One dataset (photos in .TIFF) of the iPhone XS is provided. The results of the datasets are used for a photogrammetry mesh quality comparison and a calculation time comparison. For the mesh quality comparison, visual qualitative inspections were performed on the models and the results were compared. Furthermore, all settings in the RealityCapture BETA 1.0.3.9696 ppi and Meshroom 2019 2.0 software are provided. A comparison of the quality of the photogrammetric 3D meshes was performed by comparing the rendering results. The dataset of the iPhone XS can be used to compare further photogrammetry software or single algorithms. Besides the images, the initial point cloud of the laser scanner is provided. Also included is the combined file which consists of the laser scan point cloud and the photogrammetry mesh of the end of the experiment.

Details

ISSN :
23523409
Volume :
33
Database :
OpenAIRE
Journal :
Data in brief
Accession number :
edsair.pmid.dedup....f3a817fdd6d6a15bd7a96b732eb3932d