Dynamic vehicle pose estimation and tracking based on motion feedback for LiDARs | |
Xu, Fengyu1,3; Wang, Zhiling2,3,4; Wang, Hanqi1,3; Lin, Linglong2,3,4; Liang, Huawei2,3,4 | |
刊名 | APPLIED INTELLIGENCE |
2022-05-07 | |
关键词 | Vehicle tracking Pose estimation Motion feedback Matched filtering |
ISSN号 | 0924-669X |
DOI | 10.1007/s10489-022-03576-3 |
通讯作者 | Lin, Linglong(linll@iim.ac.cn) ; Liang, Huawei(hwliang@iim.ac.cn) |
英文摘要 | This paper presents a novel dynamic vehicle tracking framework, achieving accurate pose estimation and tracking in urban environments. For vehicle tracking with laser scanners, pose estimation extracts geometric information of the target from a point cloud clustering unit, which plays an essential role in tracking tasks. However, the point cloud acquired from laser scanners only provides distance measurements to the object surface facing the sensor, leading to nonnegligible pose estimation errors. To address this issue, we take the motion information of targets as feedback to assist vehicle detection and pose estimation. In addition, the heading normalization vehicle model and a robust target size estimation method are introduced to deduce the pose of a vehicle with 2D matched filtering. Furthermore, considering the mobility of vehicles, we utilize the interactive multitude model (IMM) to capture multiple motion patterns. Compared to existing methods in the literature, our method can be applied to spatially sparse or incomplete point cloud observations. Experimental results demonstrate that our vehicle tracking framework achieves promising performance, and its real-time capability is also validated in real traffic scenarios. |
资助项目 | National Key Research and Development Program of China[2020AAA0108103] ; Key Science and Technology Project of Anhui[202103a05020007] ; Technological Innovation Project for New Energy and Intelligent Networked Automobile Industry of Anhui Province |
WOS关键词 | 3D ; SEGMENTATION ; NETWORK |
WOS研究方向 | Computer Science |
语种 | 英语 |
出版者 | SPRINGER |
WOS记录号 | WOS:000791874500001 |
资助机构 | National Key Research and Development Program of China ; Key Science and Technology Project of Anhui ; Technological Innovation Project for New Energy and Intelligent Networked Automobile Industry of Anhui Province |
内容类型 | 期刊论文 |
源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/130791] |
专题 | 中国科学院合肥物质科学研究院 |
通讯作者 | Lin, Linglong; Liang, Huawei |
作者单位 | 1.Univ Sci & Technol China, Hefei 230026, Peoples R China 2.Chinese Acad Sci, Applicat & Innovat Res Inst Robot & Intelligent M, Hefei 230088, Peoples R China 3.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230088, Peoples R China 4.Anhui Engn Lab Intelligent Driving Technol, Hefei 230088, Peoples R China |
推荐引用方式 GB/T 7714 | Xu, Fengyu,Wang, Zhiling,Wang, Hanqi,et al. Dynamic vehicle pose estimation and tracking based on motion feedback for LiDARs[J]. APPLIED INTELLIGENCE,2022. |
APA | Xu, Fengyu,Wang, Zhiling,Wang, Hanqi,Lin, Linglong,&Liang, Huawei.(2022).Dynamic vehicle pose estimation and tracking based on motion feedback for LiDARs.APPLIED INTELLIGENCE. |
MLA | Xu, Fengyu,et al."Dynamic vehicle pose estimation and tracking based on motion feedback for LiDARs".APPLIED INTELLIGENCE (2022). |
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