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Monocular Camera and IMU Integration for Indoor Position Estimation
Zhang YL(张吟龙); Tan JD(谈金东); Zeng ZM(曾子铭); Liang W(梁炜); Xia Y(夏晔)
作者部门工业控制网络与系统研究室
会议名称2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
会议日期August 26-30
会议地点Chicago, IL, USA
会议录名称2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
出版者IEEE
出版地Piscataway, NJ, USA
2014
页码1198-1201
收录类别EI ; CPCI(ISTP)
EI收录号20152100874188
WOS记录号WOS:000350044701049
产权排序1
ISBN号978-1-4244-7929-0
摘要This paper presents a monocular camera (MC) and inertial measurement unit (IMU) integrated approach for indoor position estimation. Unlike the traditional estimation methods, we fix the monocular camera downward to the floor and collect successive frames where textures are orderly distributed and feature points robustly detected, rather than using forward oriented camera in sampling unknown and disordered scenes with pre-determined frame rate and auto-focus metric scale. Meanwhile, camera adopts the constant metric scale and adaptive frame rate determined by IMU data. Furthermore, the corresponding distinctive image feature point matching approaches are employed for visual localizing, i.e., optical flow for fast motion mode; Canny Edge Detector & Harris Feature Point Detector & Sift Descriptor for slow motion mode. For superfast motion and abrupt rotation where images from camera are blurred and unusable, the Extended Kalman Filter is exploited to estimate IMU outputs and to derive the corresponding trajectory. Experimental results validate that our proposed method is effective and accurate in indoor positioning. Since our system is computationally efficient and in compact size, it's well suited for visually impaired people indoor navigation and wheelchaired people indoor localization.
语种英语
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被引频次:5[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/173321/15368
专题工业控制网络与系统研究室
作者单位1.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Konxville, TN, United States
3.Information and Control Engineering Faculty, Shenyang Jianzhu University, Shenyang, China
4.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式
GB/T 7714
Zhang YL,Tan JD,Zeng ZM,et al. Monocular Camera and IMU Integration for Indoor Position Estimation[C]. Piscataway, NJ, USA:IEEE,2014:1198-1201.
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