Augmented Reality's (AR) scope and capabilities have grown considerably in the last few years. AR applications can be run across devices such as phones, wearables, and head-mounted displays (HMDs). The increasing research and commercial efforts in HMDs capabilities allow end users to map a 3D environment and interact with virtual objects that can respond to the physical aspects of the scene. Within this context, AR is an ideal format for in-situ training scenarios. However, building such AR scenarios requires proficiency in game engine development environments and programming expertise. These difficulties can make it challenging for domain experts to create training content in AR. To combat this problem, this thesis presents strategies and guidelines for building authoring tools to generate scenario-based training experiences in AR. The authoring tools were built leveraging concepts from the 3D user interfaces and interaction techniques literature. We found from early research in the field and our experimentation that scenario and object behavior authoring are substantial aspects needed to create a training experience by an author. This work also presents a technique to author object component behaviors with high usability scores, followed by an analysis of the different aspects of authoring object component behaviors across AR, VR, and Desktop. User studies were run to evaluate authoring strategies, and the results provide insights into future directions for building AR/VR immersive authoring tools. Finally, we discuss how this knowledge can influence the development, guidelines, and strategies in the direction of a more compelling set of tools to author augmented reality SBT experiences.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2448 |
Date | 01 January 2022 |
Creators | Vargas Gonzalez, Andres |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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