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An Active Multi-Object Ultrafast Tracking System with CNN-Based Hybrid Object Detection by Qing Li; Shaopeng Hu; Kohei Shimasaki; Idaku Ishii is a Engineering article available to read on EtoBox.

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This study proposes a visual tracking system that can detect and track multiple fast-moving appearance-varying targets simultaneously with 500 fps image processing. The system comprises a high-speed camera and a pan-tilt galvanometer system, which can rapidly generate large-scale high-definition images of the wide monitored area. We developed a CNN-based hybrid tracking algorithm that can robustly track multiple high-speed moving objects simultaneously. Experimental results demonstrate that our system can track up to three moving objects with velocities lower than 30 m per second simultaneously within an 8-m range. The effectiveness of our system was demonstrated through several experiments conducted on simultaneous zoom shooting of multiple moving objects (persons and bottles) in a natural outdoor scene. Moreover, our system demonstrates high robustness to target loss and crossing situations.

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Author

Qing Li; Shaopeng Hu; Kohei Shimasaki; Idaku Ishii

Publisher

MDPI AG

Published

2023

Language

EN

Field

Engineering (Physical Sciences)