Augmented reality and inertial tracking for indoor localization in smart mobile devices

Abstract

The idea of using computers to assist people in their daily lives has been popular for a long time. Computer devices can help a user to accomplish tasks by providing important and relevant information. Therefore, there is a need to have knowledge of this information, including when and how the information is displayed, so a user can benefit from it. Mobile computer devices such as smartphones can take advantage of a wide range of sensors to analyze the user environment in order to provide useful information. With the development of faster Smartphones, recent innovations in mobile applications have changed the way users utilize their devices. In particular, higher processing power allows computationally intensive applications to run on small and portable devices, and one of these novel applications is augmented reality (AR). The increasing demand for interactive multimedia applications and services means that AR has become a significant area of interest for the mobile industry and researchers. An innovative usage of AR is to provide information based on the user location, which facilitates context-aware applications and services that can be personalized to the user profile. Various technologies based on real-time localization, positioning, tracking, and mapping using one or more built-in sensors can be utilized by AR mobile applications. The utilization of a combination of sensors helps to obtain better results by improving the stability, tracking, and operating range, as well as facilitating the creation of a blended reality environment, which provides information and services at the right time and place. This thesis includes a review of the state-of-the-art of the technology, its deployment on indoor environments using a combination of sensors (e.g., a camera, accelerometer, gyroscope, and compass), and evaluations of the methods and algorithms used for localization and tracking in mobile devices, as well as for the analysis and understanding of mobile user movements. In addition, this thesis examines the possibility of using depth-sensing technology, which will soon be available in smartphones, to support different applications, including mapping dynamic structure with AR content and the facilitation of gesture-based interaction.

Date of Award	2014
Original language	American English
Supervisor	Mohamed Zemerly (Supervisor)