Real Time Detection and Identification of UAV Abnormal Trajectory
文献类型：会议论文
| 作者 | Wang, Ziyuan1,2; Zhang, Geng1 ; Hu, Bingliang1; Feng, Xiangpeng1
|
| 出版日期 | 2020-06-26 |
| 会议日期 | 2020-06-26 |
| 会议地点 | Virtual, Online, China |
| 关键词 | Computing methodologies Artificial intelligence Computer vision Computer vision tasks |
| DOI | 10.1145/3430199.3430212 |
| 页码 | 51-56 |
| 英文摘要 | Abnormal behavior detection based on video sequence is a hot field. At the same time, monitoring and tracking the UAV (Unmanned Aerial Vehicle) and identifying its abnormal behavior are great significance for the UAV defense. This paper focuses on the detection and recognition of the UAV abnormal trajectory based on real-time video sequence. By tracking and analyzing the characteristics of the UAV, the detection and recognition of abnormal trajectory are divided into two stages. First, by analyzing the UAV's abnormal trajectory satisfying the change conditions is extracted by the quantitative analysis of the UAV's directional angle change features. Second, the normalized polar path fourier spectrum feature of abnormal trajectory is established, and the feature is combined with window search length to accelerate the classification and identification of the UAV trajectory types. Through the contrast experiment, it shows that the method in this paper has good real-time performance and accuracy for trajectory recognition with scale and translation changes. © 2020 ACM. |
| 产权排序 | 1 |
| 会议录 | Proceedings of the 2020 3rd International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2020
 |
| 会议录出版者 | Association for Computing Machinery |
| 语种 | 英语 |
| ISBN号 | 9781450375511 |
| 源URL | [http://ir.opt.ac.cn/handle/181661/94267]  |
| 专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
| 作者单位 | 1.Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an, China; 2.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Wang, Ziyuan,Zhang, Geng,Hu, Bingliang,et al. Real Time Detection and Identification of UAV Abnormal Trajectory[C]. 见:. Virtual, Online, China. 2020-06-26. |
入库方式： OAI收割
来源：西安光学精密机械研究所
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