Title: Point-Cloud-Based Aerial Fragmentation Analysis for Application in the Minerals Industry,
Abstract: This work investigates the application of Unmanned Aerial Vehicle (UAV)
technology for measurement of rock fragmentation without placement of scale
objects in the scene to determine image scale. Commonly practiced image-based
rock fragmentation analysis requires a technician to walk to a rock pile, place
a scale object of known size in the area of interest, and capture individual 2D
images. Our previous work has used UAV technology for the first time to acquire
real-time rock fragmentation data and has shown comparable quality of results;
however, it still required the (potentially dangerous) placement of scale
objects, and continued to make the assumption that the rock pile surface is
planar and that the scale objects lie on the surface plane. This work improves
our UAV-based approach to enable rock fragmentation measurement without
placement of scale objects and without the assumption of planarity. This is
achieved by first generating a point cloud of the rock pile from 2D images,
taking into account intrinsic and extrinsic camera parameters, and then taking
2D images for fragmentation analysis. This work represents an important step
towards automating post-blast rock fragmentation analysis. In experiments, a
rock pile with known size distribution was photographed by the UAV with and
without using scale objects. For fragmentation analysis without scale objects,
a point cloud of the rock pile was generated and used to compute image scale.
Comparison of the rock size distributions show that this point-cloud-based
method enables producing measurements with better or comparable accuracy
(within 10% of the ground truth) to the manual method with scale objects.