UAV Complex-Scene Single-Target Tracking Based on Improved Re-Detection Staple Algorithm

Author:

Huang Yiqing12,Huang He12,Niu Mingbo3ORCID,Miah Md Sipon34ORCID,Wang Huifeng1,Gao Tao5

Affiliation:

1. School of Electronics and Control Engineering, Chang’an University, Xi’an 710064, China

2. Xi’an Key Laboratory of Intelligent Expressway Information Fusion and Control, Chang’an University, Xi’an 710064, China

3. IVR Low-Carbon Research Institute, School of Energy and Electrical Engineering, Chang’an University, Xi’an 710064, China

4. Department of Signal Theory and Communications, University Carlos III of Madrid, Leganes, 28903 Madrid, Spain

5. School of Information Engineering, Chang’an University, Xi’an 710064, China

Abstract

With the advancement of remote sensing technology, the demand for the accurate monitoring and tracking of various targets utilizing unmanned aerial vehicles (UAVs) is increasing. However, challenges such as object deformation, motion blur, and object occlusion during the tracking process could significantly affect tracking performance and ultimately lead to tracking drift. To address this issue, this paper introduces a high-precision target-tracking method with anomaly tracking status detection and recovery. An adaptive feature fusion strategy is proposed to improve the adaptability of the traditional sum of template and pixel-wise learners (Staple) algorithm to changes in target appearance and environmental conditions. Additionally, the Moth Flame Optimization (MFO) algorithm, known for its strong global search capability, is introduced as a re-detection algorithm in case of tracking failure. Furthermore, a trajectory-guided Gaussian initialization technique and an iteration speed update strategy are proposed based on sexual pheromone density to enhance the tracking performance of the introduced re-detection algorithm. Comparative experiments conducted on UAV123 and UAVDT datasets demonstrate the excellent stability and robustness of the proposed algorithm.

Funder

International Innovation Centre Project of Shaanxi Province

Ministry of Science and Technology of China

Chang’an University Central Universities

Open Fund Project of the Key Laboratory of Information Fusion and Control of Xi’an Smart Expressway

Publisher

MDPI AG

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