Year: 2013
Type: dissertation
Abstract: Most approaches to spatial image management involve GPS or image processing. In this thesis, a sensor-focused alternative is explored. It requires user and camera tracking, particularly challenging in indoor environments. \n \nPossible indoor tracking methods are evaluated and pedestrian dead reckoning is selected. A study is conducted to evaluate sensors and choose a combination for pedestrian and camera tracking. Gyroscope and accelerometer offer comparable step detection performance, with gyroscope and tilt compensated compass providing heading data. \n \nImages taken from the same viewpoint are successfully arranged using panorama stitching without any image processing. The results compare favourably to conventional methods. While lacking visual definition of image processing methods, they can complement them if used in tandem. \n \nSensor compositing and pedestrian tracking are implemented in a unified system. Several methods for fusing compass and gyroscope data are compared, but do not produce statistically significant improvement over using just the compass. The system achieves loop closure accuracy of 91% of path length and performs consistently across multiple participants. \n \nThe final system can be used in GPS-denied locations and presents an image content independent way of managing photographs. It contributes to pedestrian tracking and image composting fields and has potential commercial uses (illustrated by an example Android app). \n
Author: Aieat Assam
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W74671736