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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2019> 28(3): 389-398
Yufeng Ji, Weixing Li, Xiaolin Li, Shikun Zhang, Feng Pan. Multi-Object Tracking with Micro Aerial Vehicle[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2019, 28(3): 389-398. doi: 10.15918/j.jbit1004-0579.18064
Citation: Yufeng Ji, Weixing Li, Xiaolin Li, Shikun Zhang, Feng Pan. Multi-Object Tracking with Micro Aerial Vehicle[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2019, 28(3): 389-398.doi:10.15918/j.jbit1004-0579.18064
shu

Multi-Object Tracking with Micro Aerial Vehicle

doi:10.15918/j.jbit1004-0579.18064
  • 1.

    School of Automation, Beijing Institute of Technology, Beijing 100081, China

  • 2.

    School of Automation, Beijing Institute of Technology, Beijing 100081, China;Industrial Technology Research Institute of Beijing Institute of Technology, Kunming 650106, China

  • Received Date:2018-04-02
    Abstract
  • A simple yet efficient tracking framework is proposed for real-time multi-object tracking with micro aerial vehicles(MAVs). It's basic missions for MAVs to detect specific targets and then track them automatically. In our method, candidate regions are generated using the salient detection in each frame and then classified by an eural network. A kernelized correlation filter(KCF) is employed to track each target until it disappears or the peak-sidelobe ratio is lower than a threshold. Besides, we define the birth and death of each tracker for the targets. The tracker is recycled if its target disappears and can be assigned to a new target. The algorithm is evaluated on the PAFISS and UAV123 datasets. The results show a good performance on both the tracking accuracy and speed.
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