Abstract
Augmented reality (AR) displays are transitioning from being primarily used in research and development settings, to being used by the general public. With this transition, these displays will be used by more people, in many different environments, and in many different contexts. Like other displays, the user's perception of virtual imagery is influenced by the characteristics of the user's environment, creating a discrepancy between the intended appearance and the perceived appearance of virtual imagery shown on the display. However, this problem is much more apparent for optical see-through AR displays, such as the HoloLens. For these displays, imagery is superimposed onto the user's view of their environment, which can cause the imagery to become transparent and washed out in appearance from the user's perspective. Any change in the user's environment conditions or in the user's position introduces changes to the perceived appearance of the AR imagery, and current AR displays do not adapt to maintain a consistent perceived appearance of the imagery being displayed. Because of this, in many environments the user may misinterpret or fail to notice information shown on the display. In this dissertation, I investigate the factors that influence user perception of AR imagery and demonstrate examples of how the user's perception is affected for applications involving user interfaces, attention cues, and virtual humans. I establish a mathematical model that relates the user, their environment, their AR display, and AR imagery in terms of luminance or illuminance contrast. I demonstrate how this model can be used to classify the user's viewing conditions and identify problems the user is prone to experience when in these conditions. I demonstrate how the model can be used to simulate changes in the user's viewing conditions and to identify methods to maintain the perceived appearance of the AR imagery in changing conditions.
Graduation Date
2023
Semester
Spring
Advisor
Welch, Gregory
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
Computer Science
Degree Program
Computer Science
Identifier
CFE0009517; DP0027521
URL
https://purls.library.ucf.edu/go/DP0027521
Language
English
Release Date
5-15-2023
Length of Campus-only Access
None
Access Status
Doctoral Dissertation (Open Access)
STARS Citation
Erickson, Austin, "Understanding, Modeling, and Simulating the Discrepancy Between Intended and Perceived Image Appearance on Optical See-Through Augmented Reality Displays" (2023). Electronic Theses and Dissertations, 2020-. 1555.
https://stars.library.ucf.edu/etd2020/1555
Acknowledgement of Grant Funding