OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling
文献类型：期刊论文
| 作者 | Zhang, Qiuyu2; Wang, Lipeng2; Li, Wanyi1 ; Meng, Hao2; Zhang, Wen2; Zhang, Zhi2; Wang, Peng1
|
| 刊名 | PATTERN RECOGNITION LETTERS
 |
| 出版日期 | 2023-10-01 |
| 卷号 | 174页码:7 |
| 关键词 | LIDAR point clouds Object tracking Gaussian sampling Candidate regions Auto-encoder |
| ISSN号 | 0167-8655 |
| DOI | 10.1016/j.patrec.2023.08.021 |
| 通讯作者 | Wang, Lipeng(wanglipeng@hrbeu.edu.cn) |
| 英文摘要 | LIDAR point clouds are less affected by the weather and possess more depth of field than 2D images. However, sparsity and disorder of point clouds bring challenges for 3D object tracking due to the difficulty in detecting and encoding. In addition, ineffective candidate proposals increase the phenomenon of the loss of target tracking or wrong target tracking. In this paper, we propose an Orientation-variant Siamese 3D object tracking network that utilizes a Detection based Sampling module to generate candidate proposals (OS-DS tracker). The Detection based Sampling module is used to cut the excessive and useless proposals. And the multivariate Gaussian sampling generates the candidate proposals when the objects are not detected. Concretely, we first pre-train PointRCNN Network to globally detect objects from LIDAR point clouds. Then the 3D detected objects are refined by Candidate Regions Sampling to generate candidate proposals. Meanwhile, to make the feature vectors more discriminative, we design an Orientation-variant Siamese Auto-encoder, i.e., tracking loss regress to the intersection over union (IOU) of the template box and the candidate region boxes. Our method is tested on the KITTI dataset and the SHIP Tracking dataset. Compared with the previous state-of-the-arts, the proposed method outperforms in vessel tracking with 5.2%/2.1% improvement in Success and Precision. |
| 资助项目 | National Natural Science Founda-tion of China[62173103] ; National Natural Science Founda-tion of China[52171299] ; Fundamental Re-search Funds for the Central Universities of China[3072022JC0402] ; Fundamental Re-search Funds for the Central Universities of China[3072022JC0403] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001075309400001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Founda-tion of China ; Fundamental Re-search Funds for the Central Universities of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53101]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Wang, Lipeng |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 2.Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Qiuyu,Wang, Lipeng,Li, Wanyi,et al. OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling[J]. PATTERN RECOGNITION LETTERS,2023,174:7. |
| APA | Zhang, Qiuyu.,Wang, Lipeng.,Li, Wanyi.,Meng, Hao.,Zhang, Wen.,...&Wang, Peng.(2023).OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling.PATTERN RECOGNITION LETTERS,174,7. |
| MLA | Zhang, Qiuyu,et al."OS-DS tracker: Orientation-variant Siamese 3D tracking with Detection based Sampling".PATTERN RECOGNITION LETTERS 174(2023):7. |
入库方式： OAI收割
来源：自动化研究所
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