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A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization
Joint Authors
Leung, Henry
Liu, Minxiang
Wang, Yuhao
Yu, Jiangnan
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-07-14
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
We present a novel feature-level data fusion method for autonomous localization in an inactive multiple reference unknown indoor environment.
Since monocular sensors cannot provide the depth information directly, the proposed method incorporates the edge information of images from a camera with homologous depth information received from an infrared sensor.
Real-time experimental results demonstrate that the accuracies of position and orientation are greatly improved by using the proposed fusion method in an unknown complex indoor environment.
Compared to monocular localization, the proposed method is found to have up to 70 percent improvement in accuracy.
American Psychological Association (APA)
Liu, Minxiang& Wang, Yuhao& Leung, Henry& Yu, Jiangnan. 2013. A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1031839
Modern Language Association (MLA)
Liu, Minxiang…[et al.]. A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization. Mathematical Problems in Engineering No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-1031839
American Medical Association (AMA)
Liu, Minxiang& Wang, Yuhao& Leung, Henry& Yu, Jiangnan. A Novel Feature-Level Data Fusion Method for Indoor Autonomous Localization. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-1031839
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1031839