@inproceedings{1b8637147e644fe89a56dc7c4b4c14b3,
title = "Design of UAV Single Object Tracking Algorithm Based on Feature Fusion",
abstract = "Considering the real-time performance and robustness of the object tracking algorithm, this paper proposes an improved tracking algorithm for single object tracking based on UAV. The algorithm uses Tiny-YOLOv3 for preliminary detection, and the detection results combine histogram of orientation gradient(HOG) and RGB histogram to extract the features. We use histogram matching to find the highest similarity between the detected candidate object and the object to be tracked to achieve the purpose of tracking. Different tracking strategies are designed when the object is stationary and moving. The experimental results show that the algorithm improves tracking accuracy and robustness while ensuring real-time tracking.",
keywords = "histogram matching, HOG, Single object tracking, Tiny-YOLOv3, UAV",
author = "Changze Li and Xiaoxiong Liu and Xingwang Zhang and Bin Qin",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9549909",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "3088--3092",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
}