| Intensity/Inertial Integration-Aided Feature Tracking on Event Cameras | |
| Li, Zeyu1; Liu, Yong2; Zhou, Feng1; Li, Xiaowan3 | |
| 2022-04-01 | |
| 发表期刊 | REMOTE SENSING
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| 卷号 | 14期号:8页码:15 |
| 摘要 | Achieving efficient and accurate feature tracking on event cameras is a fundamental step for practical high-level applications, such as simultaneous localization and mapping (SLAM) and structure from motion (SfM) and visual odometry (VO) in GNSS (Global Navigation Satellite System)-denied environments. Although many asynchronous tracking methods purely using event flow have been proposed, they suffer from high computation demand and drift problems. In this paper, event information is still processed in the form of synthetic event frames to better adapt to the practical demands. Weighted fusion of multiple hypothesis testing with batch processing (WF-MHT-BP) is proposed based on loose integration of event, intensity, and inertial information. More specifically, with inertial information acting as priors, multiple hypothesis testing with batch processing (MHT-BP) produces coarse feature-tracking solutions on event frames in a batch processing way. With a time-related stochastic model, a weighted fusion mechanism fuses feature-tracking solutions from event and intensity frames compared with other state-of-the-art feature-tracking methods on event cameras. Evaluation on public datasets shows significant improvements on accuracy and efficiency and comparable performances in terms of feature-tracking length. |
| 关键词 | event camera feature tracking intensity inertial integration |
| 资助者 | Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China |
| DOI | 10.3390/rs14081773 |
| 语种 | 英语 |
| 资助项目 | Shandong Provincial Natural Science Foundation[ZR2021QD148] ; Open Research Project[ICT2021B17] ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China |
| 资助者 | Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; Shandong Provincial Natural Science Foundation ; Shandong Provincial Natural Science Foundation ; Open Research Project ; Open Research Project ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China ; State Key Laboratory of Industrial Control Technology, Zhejiang University, China |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000787396300001 |
| 出版者 | MDPI |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://210.72.145.45/handle/361003/13828 |
| 专题 | 量子频标研究室 |
| 通讯作者 | Liu, Yong |
| 作者单位 | 1.Shandong Univ Sci & Technol, Coll Geodesy & Geomat, Qingdao 266590, Peoples R China 2.Zhejiang Univ, Inst Cyber Syst & Control, Hangzhou 310027, Peoples R China 3.Chinese Acad Sci, Natl Time Serv Ctr, Xian 710600, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Zeyu,Liu, Yong,Zhou, Feng,et al. Intensity/Inertial Integration-Aided Feature Tracking on Event Cameras[J]. REMOTE SENSING,2022,14(8):15. |
| APA | Li, Zeyu,Liu, Yong,Zhou, Feng,&Li, Xiaowan.(2022).Intensity/Inertial Integration-Aided Feature Tracking on Event Cameras.REMOTE SENSING,14(8),15. |
| MLA | Li, Zeyu,et al."Intensity/Inertial Integration-Aided Feature Tracking on Event Cameras".REMOTE SENSING 14.8(2022):15. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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