Knowledge Commons of Institute of Automation,CAS
Dynamic Rigid Bodies Mining and Motion Estimation Based on Monocular Camera | |
Gao, Xuanchang1,2; Liu, Xilong1; Cao, Zhiqiang1; Tan, Min1; Yu, Junzhi1,3 | |
发表期刊 | IEEE TRANSACTIONS ON CYBERNETICS |
ISSN | 2168-2267 |
2022-04-13 | |
页码 | 12 |
摘要 | Dynamic object perception is an important yet challenging direction in the field of robot navigation. Without any prior knowledge about motion and objects, a novel dynamic rigid bodies mining and motion estimation method based on monocular camera is proposed in this article. Different from the existing works based on sampling that associate feature points to motion hypotheses according to the reprojection errors, our work endeavors to find the intrinsic relevance among motion hypotheses. To represent this relevance, the concept of the probabilistic field on the Lie group Sim(3) manifold is introduced, which is established using random sampling. It provides a computable way for the regions on the manifold where rigid bodies possibly appear. The probability of a motion hypothesis falling on a region is expressed by its confidence. The regions with large confidences in the probabilistic field are selected as potential rigid bodies, whose corresponding feature points are further sampled for pose calculation. As a result, the randomness of sampling is reduced and the inliers for possible rigid bodies are enhanced, which guarantees the accuracy of motion estimation. On this basis, the tracking of rigid bodies is achieved. The proposed method distinguishes the feature points of dynamic objects with 3-D motion from those in the static background, thus enabling simultaneous localization and mapping (SLAM) to be initialized in dynamic environments. The experimental results on the KITTI, Hopkins 155, and MTPV62 datasets demonstrate the effectiveness. Comparison experiments indicate that our method outperforms the other methods in sensitivity of dynamic objects perception. |
关键词 | Dynamic rigid bodies Monocular camera Motion estimation Probabilistic field Region confidence |
DOI | 10.1109/TCYB.2022.3163545 |
关键词[WOS] | SEGMENTATION ; PERSPECTIVE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61633020] ; National Natural Science Foundation of China[61633020] |
WOS研究方向 | Automation & Control Systems ; Computer Science |
WOS类目 | Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
WOS记录号 | WOS:000782820900001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 机器人感知与决策 |
国重实验室规划方向分类 | 其他 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48351 |
专题 | 复杂系统认知与决策实验室_先进机器人 |
通讯作者 | Liu, Xilong |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peking Univ, Coll Engn, BIC ESAT, Dept Adv Mfg & Robot,State Key Lab Turbulence & C, Beijing 100871, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Gao, Xuanchang,Liu, Xilong,Cao, Zhiqiang,et al. Dynamic Rigid Bodies Mining and Motion Estimation Based on Monocular Camera[J]. IEEE TRANSACTIONS ON CYBERNETICS,2022:12. |
APA | Gao, Xuanchang,Liu, Xilong,Cao, Zhiqiang,Tan, Min,&Yu, Junzhi.(2022).Dynamic Rigid Bodies Mining and Motion Estimation Based on Monocular Camera.IEEE TRANSACTIONS ON CYBERNETICS,12. |
MLA | Gao, Xuanchang,et al."Dynamic Rigid Bodies Mining and Motion Estimation Based on Monocular Camera".IEEE TRANSACTIONS ON CYBERNETICS (2022):12. |
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