Augmented reality (AR) is seeing a rapid expansion into several domains due to the proliferation of more accessible and powerful hardware. While augmented reality user interfaces (AR UIs) allow the presentation of information atop the real world, this extra visual data potentially comes at a cost of increasing the visual clutter of the users' field of view, which can increase visual search time, error rates, and have an overall negative effect on performance. Visual clutter has been studied for existing display technologies, but there are no established measures of visual clutter for AR UIs which precludes the study of the effects of clutter on performance in AR UIs. The first objective of this research is to determine the applicability of extant image analysis measures of feature congestion, edge density, and sub-band entropy for measuring visual clutter in the head-worn optical see-through AR space and establish a relationship between image analysis measures of clutter and visual search time. These image analysis measures are specifically chosen to quantify clutter, as they can be applied to complex and naturalistic scenes, as is common to experience while using an optical see-through AR UI. The second objective is to examine the effects of AR UIs comprised of multiple apparent depths on user performance through the metric of visual search time. The third objective is to determine the effects of other AR UI properties such as target clutter, target eccentricity, target apparent depth and target total distance on performance as measured through visual search time. These results will then be used to develop a visual clutter score, which will rate different AR UIs against each other.
Image analysis measures for clutter of feature congestion, edge density, and sub-band entropy of clutter were correlated to visual search time when they were taken for the overall AR UI and when they were taken for a target object that a participant was searching for. In the case of an AR UI comprised of both projected and AR parts, image analysis measures were not correlated to visual search time for the constituent AR UI parts (projected or AR) but were still correlated to the overall AR UI clutter. Target eccentricity also had an effect on visual search time, while target apparent depth and target total distance from center did not. Target type and AR object percentage also had an effect on visual search time. These results were synthesized into a general model known as the "AR UI Visual Clutter Score Algorithm" using a multiple regression. This model can be used to compare different AR UIs to each other in order to identify the AR UI that is projected to have lower target visual search times. / Doctor of Philosophy / Augmented reality is a novel but growing technology. The ability to project visual information into the real-world comes with many benefits, but at the cost of increasing visual clutter. Visual clutter in existing displays has been shown to negatively affect visual search time, error rates, and general performance, but there are no established measures of visual clutter augmented reality displays, so it is unknown if visual clutter will have the same effects. The first objective of this research is to establish measures of visual clutter for augmented reality displays. The second objective is to better understand the unique properties of augmented reality displays, and how that may affect ease of use.
Measures of visual clutter were correlated to visual search time when they were taken for the augmented reality user interface, and when they were taken for a given target object within that a participant was searching for. It was also found that as targets got farther from the center of the field of view, visual search time increased, while the depth of a target from the user and the total distance a target was from the user did not. Study 1 also showed that target type and AR object percentage also had an effect on visual search time. Combining these results gives a model that can be used to compare different augmented reality user interfaces to each other.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/116220 |
| Date | 05 September 2023 |
| Creators | Flittner, Jonathan Garth |
| Contributors | Industrial and Systems Engineering, Gabbard, Joseph L., Smith, Martha Irene, Lau, Nathan Ka Ching, Agee, Philip Ryan |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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