Validation study demonstrates accurate outdoor 3D trajectory reconstruction using drone-assisted multicamera tracking, enabling scalable georeferenced dynamic analysis.
Accurate measurement of three-dimensional (3D) trajectories in outdoor environments is essential for studying complex dynamic processes such as atmospheric transport, aerial vehicle motion, and collective behavior. However, obtaining quantitative trajectory measurements over large outdoor volumes remains challenging because multicamera systems require reliable calibration and synchronization under field conditions. Here, we introduce a portable and automated drone-assisted multicamera 3D tracking (DAM3T) framework for georeferenced trajectory reconstruction. The system estimates multicamera extrinsic parameters from an autonomous drone flight without dedicated calibration markers and aligns the reconstructed coordinate system with geographic coordinates (WGS84) using real-time kinematic Global Positioning System (RTK-GPS) measurements. Validation under indoor motion-capture and outdoor RTK-GPS conditions demonstrates trajectory errors below 2%. We further demonstrate the framework through Lagrangian analysis using passive tracers, georeferenced tracking of multiple unmanned aerial vehicles, and 3D motion analysis in sports scenes. This establishes DAM3T as a scalable measurement platform that extends outdoor tracking from local-coordinate reconstruction to georeferenced measurement of complex dynamic systems.
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Kim et al. (2026) studied this question.
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