A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii
文献类型：期刊论文
| 作者 | Zhang, Guoqing7; Zhao, Yongxiang7; Fu, Ping3; Luo, Wei4,5,6,7; Shao, Quanqin2,6; Zhang, Tongzuo1,2; Yu, Zhongde7 |
| 刊名 | ECOLOGICAL INFORMATICS
 |
| 出版日期 | 2024-07-01 |
| 卷号 | 81页码:102556 |
| 关键词 | Procapra przewalskii monitoring UAV MOT GMC Deep SORT |
| DOI | 10.1016/j.ecoinf.2024.102556 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Procapra przewalskii, which inhabits plateau areas, faces the constant threat of poaching and unpredictable risks that impede its survival. The implementation of a comprehensive, real-time monitoring and tracking system for Procapra przewalskii using artificial intelligence and unmanned aerial vehicle (UAV) technology is crucial to safeguard its existence. Therefore, a UAV multi-object-tracking (MOT) system with global motion compensation (GMC) was proposed in this study. YOLOv7 and Deep SORT were employed for object detection and tracking, respectively. Furthermore, the Kalman filter (KF) in Deep SORT is optimized to enhance the accuracy of objecttracking. Moreover, a novel appearance feature-extraction network (FEN) is introduced to enable more effective multi-scale feature (MSF) extraction. In addition, a GMC module was proposed to align neighboring frames through feature matching. This facilitates the correction of the position of the target in the subsequent frame, mitigating the impact of UAV camera motion on tracking. The results demonstrated the remarkable tracking accuracy of the system. Compared with the Deep SORT model, the proposed system exhibited an increase of 6.4% in MOTA, 2.7% in MOTP, and 7.9% in IDF1. Through a comprehensive evaluation and analysis of real-world tracking scenarios, the system proposed in this study exhibits reliability in complex scenes and holds the potential to significantly enhance the protection of Procapra przewalskii from threats. |
| WOS关键词 | OBJECT DETECTION ; DEEP ; BEHAVIOR ; IMAGES |
| WOS研究方向 | Environmental Sciences & Ecology |
| WOS记录号 | WOS:001218271900001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/205205]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Luo, Wei |
| 作者单位 | 1.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810001, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101407, Peoples R China 3.Minjiang Univ, Fujian Prov Educ Dept, Key Lab Adv Mot Control, Fuzhou 350108, Peoples R China 4.Natl Joint Engn Res Ctr Space Remote Sensing Infor, Langfang 065000, Peoples R China 5.Aerosp Remote Sensing Informat Proc & Applicat Col, Langfang 065000, Peoples R China 6.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 7.North China Inst Aerosp Engn, Langfang 065000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Guoqing,Zhao, Yongxiang,Fu, Ping,et al. A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii[J]. ECOLOGICAL INFORMATICS,2024,81:102556. |
| APA | Zhang, Guoqing.,Zhao, Yongxiang.,Fu, Ping.,Luo, Wei.,Shao, Quanqin.,...&Yu, Zhongde.(2024).A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii.ECOLOGICAL INFORMATICS,81,102556. |
| MLA | Zhang, Guoqing,et al."A reliable unmanned aerial vehicle multi-target tracking system with global motion compensation for monitoring Procapra przewalskii".ECOLOGICAL INFORMATICS 81(2024):102556. |
入库方式： OAI收割
来源：地理科学与资源研究所
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