Volume XLII-4/W8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 217–223, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-217-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 217–223, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-217-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Jul 2018

11 Jul 2018

THE USE OF THE UAV IMAGES FOR THE BUILDING 3D MODEL GENERATION

G. Vacca1, G. Furfaro2, and A. Dessì1 G. Vacca et al.
  • 1Dept. of Civil Engineering, Environmental and Architecture, University of Cagliari (CA), Italy
  • 2STF land & sea survey Brindisi, Italy

Keywords: UAV, photogrammetry, oblique images, SfM, open source, VisualSfM

Abstract. The growing interest in recent years in Unmanned Aerial Vehicles (UAVs) by the scientific community, software developers, and geomatics professionals, has led these systems to be used more and more widely, in different fields of engineering and architecture. This is thanks, above all, to their flexibility of use and low cost compared to traditional photogrammetric flights using expensive metric digital cameras or LiDAR sensors. In recent years, UAVs have also been used in the field of monitoring and inspection of public or private buildings that are remarkable in terms of size and architecture. This is mainly due to the focus a sustainability and resource efficiency in the building and infrastructure sector, which aims to extend their lifetimes. Through the use of remote checking using UAVs, the monitoring and inspection of buildings can be brought to a new level of quality and saving.

This paper focuses on the processing and study of 3D models obtained from images captured by an UAV. In particular, the authors wanted to study the accuracy gains achieved in the building 3D model obtained with both nadir and oblique UAV flights. The images from the flights were processed using Structure-for Motion-based approach for point cloud generation using dense image-matching algorithms implemented in an open source software. We used the open source software VisualSfM, developed by Chanchang Wu in collaboration with the University of Washington and Google. The dense matching plug-in integrated in its interface, PMVS/CMVS, made by Yasutaka Furukawa, was employed to generate the dense cloud. The achieved results were compare with those gained by Photoscan software by Agisoft and with 3D model from the Terrestrial Laser Scanner (TLS) survey.