You are here


Title: MAR: Mobile Augmented Reality in Indoor Environment.

Inaccessible until Sep 27, 2020 due to copyright restrictions.

Name(s): Alahmadi, Mohammad Neal, author
Yang, Jie, professor directing thesis
Mascagni, Michael, committee member
Haiduc, Sonia, committee member
Florida State University, degree granting institution
College of Arts and Sciences, degree granting college
Department of Computer Science, degree granting department
Type of Resource: text
Genre: Text
Master Thesis
Issuance: monographic
Date Issued: 2017
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource (52 pages)
Language(s): English
Abstract/Description: For decades, augmented reality has been used to allow a person to visualize an overlay of annotations, videos, and images on physical objects using a camera. Due to the high computational processing cost that is required to match an image from among an enormous number of images, it has been daunting to use the concept of augmented reality on a smartphone without significant processing delays. Although the Global Positioning System (GPS) can be very useful for the outdoor localization of an object, GPS is not suitable for indoor localization. To address the problem of indoor localization, we propose using mobile augmented reality in an indoor environment. Since most smartphones have many useful sensors such as accelerometers, magnetometers and Wi-Fi sensors, we can leverage these sensors to locate the phone’s location, the phone’s field of view, and the phone’s angle of view. Using Mobile Augmented Reality (MAR) based on processing data from several smartphone sensors, we can achieve indoor localization with reduced processing time. We tested MAR in simulated environments, and deployed the system in the Love building (LOV) at Florida State University. We used 200 images in the simulated environment, and compared the matching processing time between multiple object recognition algorithms and reduced the matching time from 2.8 seconds to only 0.17 second using a brisk algorithm.
Identifier: FSU_FALL2017_Alahmadi_fsu_0071N_13939 (IID)
Submitted Note: A Thesis submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Spring Semester 2017.
Date of Defense: April 26, 2017.
Keywords: Augmented Reality, Indoor localization, Object Recognition, Smartphone
Bibliography Note: Includes bibliographical references.
Advisory Committee: Jie Yang, Professor Directing Thesis; Michael Mascagni, Committee Member; Sonia Haiduc, Committee Member.
Subject(s): Computer science
Persistent Link to This Record:
Owner Institution: FSU

Choose the citation style.
Alahmadi, M. N. (2017). MAR: Mobile Augmented Reality in Indoor Environment. Retrieved from