Improvement of UAV-Photogrammetric Survey Accuracy Using Point Feature Constraints of Markers

• Published in: Journal of the Indian Society of Remote Sensing
• Main Authors: Xing, Lei, Li, Yufu, Yue, Chonglun
• Format: Journal Article
• Language: English
• Published: 22.07.2025
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-025-02246-4

Current keypoint-based approaches used in Unmanned Aerial Vehicle (UAV) photogrammetric surveys cannot control the error propagation effectively due to the sub-optimal number of Ground Control Points (GCPs) placed within the surveyed area. Spurred by this issue, this paper introduces a marker system that provides many precise projections of artificial markers as point feature constraints, thereby improving the accuracy of UAV-based photogrammetry. Specifically, we introduce a marker system with colored circles and white backgrounds and the corresponding detection algorithms to quickly suppress background interferences using different color spaces for accurate marker localization. The first experiment demonstrates that the proposed marker system has a better detection performance than current marker systems used in aerial surveying projects. Additionally, a second experiment reveals that, in cases with only 4 GCPs, the proposed marker system significantly improves the accuracy of the UAV-photogrammetric survey. Compared to Agisoft Metashape, adding additional point feature constraints to the markers increases the accuracy of Check Points (CPs) in the X, Y, and Z directions by 37.5%, 23.0%, and 78.2%, respectively.