Robust 6-DoF Pose Estimation under Hybrid Constraints

doi:10.3390/s22228758

CIOMP OpenIR

	Robust 6-DoF Pose Estimation under Hybrid Constraints
	H. Ren; L. Lin; Y. J. Wang and X. Dong
	2022
发表期刊	Sensors
卷号	22 期号:22 页码:20
摘要	To solve the problem of the insufficient accuracy and stability of the two-stage pose estimation algorithm using heatmap in the problem of occluded object pose estimation, a new robust 6-DoF pose estimation algorithm under hybrid constraints is proposed in this paper. First, a new loss function suitable for heatmap regression is formulated to improve the quality of the predicted heatmaps and increase keypoint accuracy in complex scenes. Second, the heatmap regression network is expanded and a translation regression branch is added to constrain the pose further. Finally, a robust pose optimization module is used to fuse the heatmap and translation estimates and improve the pose estimation accuracy. The proposed algorithm achieves ADD(-S) accuracy rates of 93.5% and 46.2% on the LINEMOD dataset and the Occlusion LINEMOD dataset, which are better than other state-of-the-art algorithms. Compared with the conventional two-stage heatmap-based pose estimation algorithms, the mean estimation error is greatly reduced, and the stability of pose estimation is improved. The proposed algorithm can run at a maximum speed of 22 FPS, thus constituting both a performant and efficient method.
DOI	10.3390/s22228758
URL	查看原文
收录类别	sci ; ei
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67066
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	H. Ren,L. Lin,Y. J. Wang and X. Dong. Robust 6-DoF Pose Estimation under Hybrid Constraints[J]. Sensors,2022,22(22):20.
APA	H. Ren,L. Lin,&Y. J. Wang and X. Dong.(2022).Robust 6-DoF Pose Estimation under Hybrid Constraints.Sensors,22(22),20.
MLA	H. Ren,et al."Robust 6-DoF Pose Estimation under Hybrid Constraints".Sensors 22.22(2022):20.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Robust 6-DoF Pose Es（4079KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载