Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Highly Accurate and Reliable Tracker for UAV-Based Herd Monitoring

Wei Luo
ORCID logo ,
Guoqing Zhang
,
Quanqin Shao
,
Xiaoliang Li
,
Zhiguo Wang
* ,
Xia Zhu
,
Zihui Zhao
,
Longfang Duan
,
Ke Liu
,
Dongliang Wang
ORCID logo ,
Xiongyi Zhang
,
Yongxiang Zhao
,
Jiandong Liu
,
Zhongde Yu
Version 1 : Received: 23 June 2023 / Approved: 23 June 2023 / Online: 23 June 2023 (11:53:25 CEST)

How to cite: Luo, W.; Zhang, G.; Shao, Q.; Li, X.; Wang, Z.; Zhu, X.; Zhao, Z.; Duan, L.; Liu, K.; Wang, D.; Zhang, X.; Zhao, Y.; Liu, J.; Yu, Z. Highly Accurate and Reliable Tracker for UAV-Based Herd Monitoring. Preprints 2023, 2023061669. https://doi.org/10.20944/preprints202306.1669.v1 Luo, W.; Zhang, G.; Shao, Q.; Li, X.; Wang, Z.; Zhu, X.; Zhao, Z.; Duan, L.; Liu, K.; Wang, D.; Zhang, X.; Zhao, Y.; Liu, J.; Yu, Z. Highly Accurate and Reliable Tracker for UAV-Based Herd Monitoring. Preprints 2023, 2023061669. https://doi.org/10.20944/preprints202306.1669.v1

Abstract

It is a challenging and meaningful task to carry out drone-based livestock monitoring in high-altitude and cold regions. The purpose of AI is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and DeepSORT algorithms for target detection and tracking, respectively. To address the existing problems of the DeepSORT algorithm, the following two optimizations are made: (1) Optical flow is used to compensate the Kalman filter for improvement of the prediction accuracy; (2) A low-confidence trajectory filtering method is adopted to reduce the influence of unreliable detection on target tracking. In addition, an visual servo controller for the UAV is designed to enable the automated tracking task. Finally, the system is tested using the Tibetan yaks living in the Tibetan Plateau as the tracking targets, and the results reveal the real-time multiple tracking ability and the ideal visual servo effect of the proposed system.

Keywords

Livestock monitoring; Open source UAV; Depth sorting; Kalman filter; Optical flow; Visual servo

Subject

Environmental and Earth Sciences, Remote Sensing

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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