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Long-Term Target Tracking for UAV Based on Correlation Filter

  • Qiao Xiao
  • Qinyu Zhang
  • Boqian Wu
  • Xiao Han
  • Xi Wu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)

Abstract

During UAV target tracking, there still exist some issues such as severe deformation, scale variance, occlusion and even fast motion. In this paper, we propose a more stable, real-time and long-term target tracking algorithm based on correlation filter for these problems. Our proposed tracker mainly included the movement and scale transformation module, which can achieves the precise area of target by combining different scale transformation based on multiple position points. In addition, we exploit the keypoint-based method to solve the redetection issue caused by target disappearance in the UAV long-term tracking process, which ensure stability of the entire system. In this paper, we verify our algorithm on the representative UAV data set called UAV123. The experimental results show that our tracker performs superiorly against several traditional methods at speed of 26 frames per second during tracking.

Keywords

UAV tracking Long-term Correlation filter Redetection Keypoint 

Notes

Acknowledgements

This work was supported in part by the National Natural Sciences Foundation of China (NSFC) under Grant 61525103, and the Shenzhen Fundamental Research Project under Grant JCYJ20150930150304185.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Qiao Xiao
    • 1
  • Qinyu Zhang
    • 1
  • Boqian Wu
    • 1
  • Xiao Han
    • 1
  • Xi Wu
    • 1
  1. 1.Communications Engineering Research Center, Harbin Institute of Technology Shenzhen Graduate SchoolShenzhenChina

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