Research on Real-Time Tracking Algorithm for Multi-Objects of Shipboard Aircraft Based on Detection
For safe guidance and real-time monitoring of the shipboard aircraft during the operation, for traditional detection-based object tracking algorithms has poor tracking performance and susceptibility to interference, proposed the multi-object real-time tracking algorithm of shipboard aircraft that co...
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| Formato: | article |
| Lenguaje: | ZH |
| Publicado: |
Editorial Office of Aero Weaponry
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4e393df087fc43feab688c78a101d57f |
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| Sumario: | For safe guidance and real-time monitoring of the shipboard aircraft during the operation, for traditional detection-based object tracking algorithms has poor tracking performance and susceptibility to interference, proposed the multi-object real-time tracking algorithm of shipboard aircraft that combined YOLO v3 object detection algorithm and Kalman filtering. The anchor size of the original YOLO v3 algorithm is optimized by the K-means clustering algorithm, combined with the Kalman filter algorithm to achieve effective tracking of shipboard aircraft objects, and compared with object tracking algorithm based on optical flow and SORT multi-object tracking algorithm on self-built shipboard aircraft tracking dataset and MOT16 multi-object tracking dataset. The results show that the tracking algorithm proposed is more accurate, robust and stable, and has strong adaptability when the object frame width and height change suddenly. |
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