SIA OpenIR  > 工业控制网络与系统研究室
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)
Department工业控制网络与系统研究室
Conference Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Conference DateAugust 26-30
Conference PlaceChicago, IL, USA
Source Publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2014
Pages1198-1201
Indexed ByEI ; CPCI(ISTP)
EI Accession number20152100874188
WOS IDWOS:000350044701049
Contribution Rank1
ISBN978-1-4244-7929-0
AbstractThis 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.
Language英语
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/15368
Collection工业控制网络与系统研究室
Affiliation1.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
Recommended Citation
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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