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An Automatic and Accurate Method for Marking Ground Control Points in Unmanned Aerial Vehicle Photogrammetry

Linghao Kong, Ting Chen, Taibo Kang, Qing Chen, Di Zhang

2022IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing16 citationsDOIOpen Access PDF

Abstract

Owing to the rapid development of unmanned aerial vehicle (UAV) technology and various photogrammetric software, UAV photogrammetry projects are becoming increasingly automated. However, marking ground control points (GCPs) in current UAV surveys still generally needs to be manually completed, which brings the problem of inefficiency and human error. Based on the characteristics of UAV photogrammetry, a novel type of circular coded target with its identification and decoding algorithm is proposed to realize an automatic and accurate approach for marking GCPs. UAV survey experiments validate the feasibility of the proposed method, which has comparative advantages in efficiency, robustness, and accuracy over traditional targets. Additionally, we conducted experiments to discuss the effects of projection size and viewing angle, number of coded bits, and environmental conditions on the proposed method. The results show that it can achieve robust identification and accurate positioning even under challenging conditions, and a smaller number of coded bits is recommended for better robustness.

Topics & Concepts

PhotogrammetryRobustness (evolution)Computer scienceComputer visionArtificial intelligenceSoftwareIdentification (biology)GeneBotanyBiologyBiochemistryChemistryProgramming language3D Surveying and Cultural HeritageRemote Sensing and LiDAR ApplicationsRobotics and Sensor-Based Localization
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