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Improvement and Implementation of Correlation Filter Tracking Algorithm Based on Embedded GPU

  • XU Zhuo 1 ,
  • KANG Junrui 1 ,
  • YUAN Bo 1 ,
  • HAN Dongyan 1 ,
  • DANG Qingxin 2
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  • 1 Xi’an Mordern Control Technology Research Institute, Xi’an 710065, China
  • 2 School of Management, Xi’an University of Science and Technology, Xi’an 710065, China

Received date: 2022-03-29

  Online published: 2025-05-29

Abstract

In order to solve the key and difficult problems in the target tracking task, such as long-term occlusion, scale change, field of view jitter, strong real-time requirements, etc., based on the correlation filtering framework, a multi-scale feature adaptive update target tracking algorithm is proposed. Multi-scale features are used to search for targets, and template features are adaptively updated to achieve stable target tracking in scenes such as occlusion and field of view jitter. At the same time, the algorithm is accelerated on the embedded GPU, which considerly improves the tracking speed while ensuring the tracking accuracy, and realizes real-time tracking on embedded devices. Finally, the test is carried out on the OTB dataset and self-collected video. The results show that the improved algorithm has good robustness in the scenes of target occlusion, scale change, field of view jitter, etc. At the same time, it can reach 50 帧/s on embedded devices. The tracking speed meets the requirements of high complexity and strong real-time when the target tracking task is implemented in embedded devices.

Cite this article

XU Zhuo , KANG Junrui , YUAN Bo , HAN Dongyan , DANG Qingxin . Improvement and Implementation of Correlation Filter Tracking Algorithm Based on Embedded GPU[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2022 , 42(4) : 97 -103 . DOI: 10.15892/j.cnki.djzdxb.2022.04.018

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