Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W4, 313-320, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W4-313-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
26 Aug 2015
UAV-BASED POINT CLOUD GENERATION FOR OPEN-PIT MINE MODELLING
M. Shahbazi1, G. Sohn2, J. Théau1, and P. Ménard3 1Dept. of Applied Geomatics, Université de Sherbrooke, Boul. de l'Université, Sherbrooke, Québec, Canada
2Dept. of Geomatics Engineering, York University, Keele Street, Toronto, Ontario, Canada
3Centre de géomatique du Québec, Saguenay, Québec, Canada
Keywords: Unmanned Aerial Vehicle, System Integration, Sensor Calibration, Structure from Motion, Sparse and Dense Matching, Open-Pit Mine, Three-dimensional Modelling Abstract. Along with the advancement of unmanned aerial vehicles (UAVs), improvement of high-resolution cameras and development of vision-based mapping techniques, unmanned aerial imagery has become a matter of remarkable interest among researchers and industries. These images have the potential to provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modelling. In this paper, we present our theoretical and technical experiments regarding the development, implementation and evaluation of a UAV-based photogrammetric system for precise 3D modelling. This system was preliminarily evaluated for the application of gravel-pit surveying. The hardware of the system includes an electric powered helicopter, a 16-megapixels visible camera and inertial navigation system. The software of the system consists of the in-house programs built for sensor calibration, platform calibration, system integration and flight planning. It also includes the algorithms developed for structure from motion (SfM) computation including sparse matching, motion estimation, bundle adjustment and dense matching.
Conference paper (PDF, 5682 KB)


Citation: Shahbazi, M., Sohn, G., Théau, J., and Ménard, P.: UAV-BASED POINT CLOUD GENERATION FOR OPEN-PIT MINE MODELLING, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W4, 313-320, https://doi.org/10.5194/isprsarchives-XL-1-W4-313-2015, 2015.

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