ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 135-139, 2017
https://doi.org/10.5194/isprs-annals-IV-4-W4-135-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
13 Nov 2017
UAV AND COMPUTER VISION, DETECTION OF INFRASTRUCTURE LOSSES AND 3D MODELING
V. Barrile1, G. Bilotta2, and A. Nunnari1 1Geomatics Lab, DICEAM, Università Mediterranea di Reggio Calabria, 89123 loc. Feo di Vito, Reggio Calabria, Italy
2Dept. of Planning, IUAV University of Venice, Santa Croce 191, Tolentini 30135 Venice, Italy
Keywords: 3D modeling, Structure from Motion, Infrastructures, Civil buildings, Degradation of buildings, Monitoring, UAV Abstract. The degradation of buildings, or rather the decline of their initial performances following external agents both natural (cold-thaw, earthquake, salt, etc.) and artificial (industrial field, urban setting, etc.), in the years lead to the necessity of developing Non-Destructive Testing (NDT) intended to give useful information for an explanation of a potential deterioration without damaging the state of buildings. An accurate examination of damages, of the repeat of cracks in condition of similar stress, indicate the existence of principles that control the creation of these events. There is no doubt that a precise visual analysis is at the bottom of a correct evaluation of the building.

This paper deals with the creation of 3D models based on the capture of digital images, through autopilot flight UAV, for civil buildings situated on the area of Reggio Calabria. The following elaboration is done thanks to the use of commercial software, based on specific algorithms of the Structure from Motion (SfM) technique. SfM represents an important progress in the aerial and terrestrial survey field obtaining results, in terms of time and quality, comparable to those achievable through more traditional data capture methodologies.

Conference paper (PDF, 1179 KB)


Citation: Barrile, V., Bilotta, G., and Nunnari, A.: UAV AND COMPUTER VISION, DETECTION OF INFRASTRUCTURE LOSSES AND 3D MODELING, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W4, 135-139, https://doi.org/10.5194/isprs-annals-IV-4-W4-135-2017, 2017.

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