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|Title:||Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification||Authors:||Srigrarom, S
|Issue Date:||20-Jan-2021||Publisher:||IEEE||Citation:||Srigrarom, S, Sie, NJL, Cheng, H, Chew, KH, Lee, M, Ratsamee, P (2021-01-20). Multi-camera Multi-drone Detection, Tracking and Localization with Trajectory-based Re-identification. 2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP). ScholarBank@NUS Repository. https://doi.org/10.1109/ICA-SYMP50206.2021.9358454||Abstract:||This paper presents a real-time multiple camera system for detecting, tracking and localizing multiple moving drones simultaneously in a 3 dimension space. The distinct feature of the system is in its target re-identification process, which provides for information fusion among cameras based on the targets' trajectories and relative locations. Drones are detected by the multiple camera system based on motion-based blob detection, and the 2D locations of each drone in individual camera frames are tracked by A geometry- and camera-based model. From the paths of the tracked drones, their trajectories are examined using drone track feature variable. Cross-correlated among cameras for object re-identifications will allow the individual 2D position information to be integrated into overall global 3D positions of all the tracked drones from all cameras. Preliminary outdoor flight demonstrations with 2 drones flying in formation and using 3 cameras show optimal results. The system is able to detect, track, localize and re-identifying individual drone with average positional error of 8%.||Source Title:||2021 Second International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP)||URI:||https://scholarbank.nus.edu.sg/handle/10635/217679||ISBN:||9781728187600||DOI:||10.1109/ICA-SYMP50206.2021.9358454|
|Appears in Collections:||Staff Publications|
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|ICA_SYMP2021_Multi_camera_system_for_3D_drone_tracking__localization_and_identification.pdf||Published version||1.2 MB||Adobe PDF|
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