ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume X-4-2024
https://doi.org/10.5194/isprs-annals-X-4-2024-333-2024
https://doi.org/10.5194/isprs-annals-X-4-2024-333-2024
18 Oct 2024
 | 18 Oct 2024

A Virtual Reality Tool for Accuracy Assessment of 3D Models in an Immersive Virtual Environment

Bala Subramaniyam, Dharshan Shylesh, Jaganathan Ramasamy, and Navin Kumar

Keywords: 3D Textured Models, Unmanned Aerial Vehicles, Accuracy Assessment, Immersive Virtual Reality, Unity Game Engine

Abstract. Accurate validation and assessment techniques are essential for ensuring the reliability of spatial reconstructions derived from photogrammetry, enabling well-informed decision-making across diverse domains. This study presents a Virtual Reality (VR) based accuracy assessment tool tailored for evaluating the accuracy and quality of 3D models generated by Unmanned Aerial Vehicles (UAVs). Leveraging the Unity game engine platform, our workflow entails three key steps: aligning real-world coordinates with an arbitrary Unity coordinate system, transforming the positions of Ground Control Points (GCPs) from field survey to the arbitrary system using a reference GCP, and marking observed points on the 3D models. Absolute and Relative Root Mean Square Errors (RMSE), Mean Errors (ME), and Standard Deviation of errors (SD) are computed within the virtual environment via the game object transform properties. The error distributions around each GCP are visually depicted using Unity game engine components for enhanced interaction and comprehension. The efficacy of the tool is validated through experimentation on four 3D models generated from varying camera angles during UAV data capture. The tool provides the opportunity to directly interact with the 3D models and visualize the errors, which is quite distinct from traditional methods. Using the developed tool, results were obtained to indicate that configurations employing camera angles of 60° + 75º exhibit notable performance in terms of relative and absolute accuracy.