Validating RealityCapture for Point cloud Creation Using sUAS Imagery

Abstract

<div class="section abstract"><div class="htmlview paragraph">Creating a 3-dimensional environment using imagery from small unmanned aerial systems (sUAS, or unmanned aerial vehicles -UAVs, or colloquially, drones) has grown in popularity recently in accident reconstruction. In this process, ground control points are placed at an accident scene and an sUAS is flown over an accident site and a series of overlapping, high resolution images are taken of the site. Those images and ground control points are then loaded onto a computer and processed using photogrammetric software to create a 3-dimensional point cloud or mesh of the site, which then can be used as a tool for recreating an accident scene. Many software packages have been created to perform these tasks, and in this paper, the authors examine RealityCapture, a newer photogrammetric software, to evaluate its accuracy for the use in accident reconstruction. It is the authors’ experience that RealityCapture may at times produce point clouds with less noise that other software packages. To do so, Propeller Aeropoints were placed along a stretch of road to provide ground control points for the photogrammetric software and an sUAS was used to take a series of overlapping aerial images of the road. The pictures and ground control points were then processed using Pix4Dmapper, a validated and widely used photogrammetric software package, and a point cloud was created. The same process was then performed in RealityCapture. The two resulting point clouds were then compared using Cloud Compare software. Through this process, the authors determined that RealityCapture’s algorithm for creating a point cloud based on overlapping images is comparable to Pix4Dmapper’s algorithm, and is adequate for use in accident reconstruction.</div></div>