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Augmented reality-based vision-aid indoor navigation system in GPS denied environment
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Paper Abstract

High accuracy localization and user positioning tracking is critical in improving the quality of augmented reality environments. The biggest challenge facing developers is localizing the user based on visible surroundings. Current solutions rely on the Global Positioning System (GPS) for tracking and orientation. However, GPS receivers have an accuracy of about 10 to 30 meters, which is not accurate enough for augmented reality, which needs precision measured in millimeters or smaller. This paper describes the development and demonstration of a head-worn augmented reality (AR) based vision-aid indoor navigation system, which localizes the user without relying on a GPS signal. Commercially available augmented reality head-set allows individuals to capture the field of vision using the front-facing camera in a real-time manner. Utilizing captured image features as navigation-related landmarks allow localizing the user in the absence of a GPS signal. The proposed method involves three steps: a detailed front-scene camera data is collected and generated for landmark recognition; detecting and locating an individual’s current position using feature matching, and display arrows to indicate areas that require more data collects if needed. Computer simulations indicate that the proposed augmented reality-based vision-aid indoor navigation system can provide precise simultaneous localization and mapping in a GPS-denied environment.

Paper Details

Date Published: 13 May 2019
PDF: 10 pages
Proc. SPIE 10993, Mobile Multimedia/Image Processing, Security, and Applications 2019, 109930P (13 May 2019); doi: 10.1117/12.2519224
Show Author Affiliations
Srijith Rajeev, Tufts Univ. (United States)
Qianwen Wan, Tufts Univ. (United States)
Kenny Yau, Tufts Univ. (United States)
Karen Panetta, Tufts Univ. (United States)
Sos Agaian, The City Univ. of New York (United States)


Published in SPIE Proceedings Vol. 10993:
Mobile Multimedia/Image Processing, Security, and Applications 2019
Sos S. Agaian; Vijayan K. Asari; Stephen P. DelMarco, Editor(s)

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