Project Director

Liang, Yu

Department

Dept. of Computer Science and Engineering

Publisher

University of Tennessee at Chattanooga

Place of Publication

Chattanooga (Tenn.)

Abstract

Augmented Reality (AR) and Unmanned Ariel Vehicles (UAVs) are fast advancing technologies, and this research seeks to combine them to offer an effective, user friendly approach for monitoring infrastructure. Drones provide a means to easily access otherwise difficult to reach locations and visualize useful information with Augmented Reality. A UAV employs a wide-angle view and, when paired with AR, this will enable the user to better complete their task by effortlessly providing the critical information they need in the most intuitive way possible. This research is particularly applicable for civil applications such as construction and monitoring of difficult to access locations. The background for these technologies and applications will be discussed in the next section, but this research is unique in its combined and interactive application of AR and drone technology. Many existing techniques which are discussed in this paper already exist for general applications of AR. Using a drone feed compared to a relatively fixed camera creates many barriers to the AR process. This research explores how existing techniques perform under these conditions, such as fast moving cameras and complex environments that drones often face. This research also explores potential methods for improving accuracy for AR objects created on a Drone feed. Existing technology such as object tracking and image filtering are used to improve accuracy. Other simple mathematical methods are used, such as Kalman Filtering and data smoothing algorithms, to improve the appearance of the AR object in the frame.

Degree

B. S.; An honors thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Bachelor of Science.

Date

5-2020

Subject

Augmented reality; Drone aircraft

Keyword

Augmented Reality; Drone; OpenCV

Discipline

Aeronautical Vehicles | Computer Engineering

Document Type

Theses

Extent

ii, 29 leaves

DCMI Type

Text

Language

English

Rights

http://rightsstatements.org/vocab/InC/1.0/

License

http://creativecommons.org/licenses/by/4.0/

thesis_main.py (8 kB)
main python source

bridge.mp4 (37309 kB)
video for python code option 1

city.mp4 (13757 kB)
video for python code option 2

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