Citation

Choi J, Yeum CM, Dyke SJ, Jahanshahi MR. Sensors (Basel) 2018; 18(9): s18093017.

Affiliation

Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA. jahansha@purdue.edu.

Copyright

(Copyright © 2018, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s18093017

PMID

30205621

Abstract

After a disaster strikes an urban area, damage to the façades of a building may produce dangerous falling hazards that jeopardize pedestrians and vehicles. Thus, building façades must be rapidly inspected to prevent potential loss of life and property damage. Harnessing the capacity to use new vision sensors and associated sensing platforms, such as unmanned aerial vehicles (UAVs) would expedite this process and alleviate spatial and temporal limitations typically associated with human-based inspection in high-rise buildings. In this paper, we have developed an approach to perform rapid and accurate visual inspection of building façades using images collected from UAVs. An orthophoto corresponding to any reasonably flat region on the building (e.g., a façade or building side) is automatically constructed using a structure-from-motion (SfM) technique, followed by image stitching and blending. Based on the geometric relationship between the collected images and the constructed orthophoto, high-resolution region-of-interest are automatically extracted from the collected images, enabling efficient visual inspection. We successfully demonstrate the capabilities of the technique using an abandoned building of which a façade has damaged building components (e.g., window panes or external drainage pipes).

Language: en

Keywords

image localization; orthophoto generation; post-event visual evaluation; unmanned aerial vehicle