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Orientation estimation using visual and inertial sensors
Zhang YL(张吟龙); Liang W(梁炜); Li Y(李杨); An HB(安海博); Tan JD(谈金东)
作者部门工业控制网络与系统研究室
会议名称2015 IEEE International Conference on Information and Automation
会议日期Augest 8-10, 2015
会议地点Lijiang, China
会议录名称2015 IEEE International Conference on Information and Automation
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码1871-1876
收录类别EI ; CPCI(ISTP)
EI收录号20161102092592
WOS记录号WOS:000380562200345
产权排序1
ISBN号978-1-4673-9104-7
关键词Orientation Estimate Inertial Measurement Unit Monocular Camera Nearest Neighbor Locality Constraint
摘要This paper presents an orientation estimate scheme using monocular camera and inertial measurement units (IMUs). Unlike the traditional wearable orientation estimation methods, our proposed approach combines both of these two modalities in a novel pattern. Firstly, two visual correspondences between consecutive frames are selected that not only meet the requirement of descriptor similarity constraint, but satisfy the locality constraints, which is under the assumption that the correspondence will be taken as an inlier if their nearest-neighbor feature-point counterparts are within the predefined thresholds with respect to the objective feature-point counterpart. Secondly, these two selected correspondences from visual sensor and quaternions from inertial sensor are jointly employed to derive the initial body poses. Thirdly, a coarse-to-fine procedure proceeds in removing visual false matches and estimating body poses iteratively using Expectation Maximization (EM). Ultimately, the optimal orientation estimation is achieved. Experimental results validate that our proposed method is effective and well suited for wearable orientation estimate.
语种英语
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17397
专题工业控制网络与系统研究室
作者单位1.Key Lab of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Konxville, TN, United States
推荐引用方式
GB/T 7714
Zhang YL,Liang W,Li Y,et al. Orientation estimation using visual and inertial sensors[C]. Piscataway, NJ, USA:IEEE,2015:1871-1876.
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