Orientation estimation using visual and inertial sensors
文献类型：会议论文
| 作者 | Zhang YL(张吟龙) ; Liang W(梁炜); Li Y(李杨); An HB(安海博); Tan JD(谈金东)
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| 出版日期 | 2015 |
| 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 |
| 关键词 | Orientation Estimate Inertial Measurement Unit Monocular Camera Nearest Neighbor locality constraint |
| 页码 | 1871-1876 |
| 中文摘要 | 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. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | 2015 IEEE International Conference on Information and Automation
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| 会议录出版者 | IEEE |
| 会议录出版地 | Piscataway, NJ, USA |
| 语种 | 英语 |
| ISBN号 | 978-1-4673-9104-7 |
| WOS记录号 | WOS:000380562200345 |
| 源URL | [http://ir.sia.cn/handle/173321/17397]  |
| 专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
| 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]. 见:2015 IEEE International Conference on Information and Automation. Lijiang, China. Augest 8-10, 2015. |
入库方式： OAI收割
来源：沈阳自动化研究所
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