Advancements in open-source photogrammetry with a point cloud standpoint

Abstract

Exploiting photogrammetric computer vision techniques to generate point cloud data for 3D scene understanding has seen many research improvements in the last decade. Open-source research and algorithm development have provided benefits and intellectual capacity to researchers and developers for understanding and providing multiple solutions to problems from different perspectives. This study focuses on the open-source domain for photogrammetry and is trying to provide a walkthrough for the recent developments in extracting 3D information from 2D images with the context of point clouds. Four different free and open-source software (VisualSFM, WebODM, Colmap, Meshroom) were studied from the perspective of their point cloud generation capability and photogrammetric workflow to provide a comparative assessment in this research. Each software is also assessed for their usability and workflow functions. UAV-based photographs were acquired for the study area and using the same datasets and default parameters in each software, dense photogrammetric point clouds were generated using their own photogrammetric workflow. For each of these dense point clouds, an assessment of their quality and enriched information based on some robust parameters is done.