Spatial referencing denotes the act of referring to a location or an object in space. Since it is often essential in different collaborative activities, good support for spatial referencing could lead to exceptional collaborative experience and performance. Augmented Reality (AR) aims to enhance daily activities and tasks in the real world, including various collaborations and social interactions. Good support for accurate and rapid spatial referencing in collaborative AR often requires detailed environment 3D information, which can be critical for the system to acquire as constrained by current technology. This dissertation seeks to address the issues related to spatial referencing in collaborative AR through 3D user interface design and different experiments. Specifically, we start with investigating the impact of poor spatial referencing on close-range, co-located AR collaborations. Next, we propose and evaluate different pointing ray techniques for object reference at a distance without knowledge from the physical environment. We further introduce marking techniques aiming to accurately acquire the position of an arbitrary point in 3D space that can be used for spatial referencing. Last, we provide a systematic assessment of an AR collaborative application that supports efficient spatial referencing in remote learning to demonstrate its benefit. Overall, the dissertation provides empirical evidence of spatial referencing challenges and benefits to collaborative AR and solutions to support adequate spatial referencing when model information from the environment is missing. / Doctor of Philosophy / People often exchange spatial information about objects when they work together. Example phrases include: ``put that there'', or ``pick the third object from left''. On the other hand, Augmented Reality (AR) is the technology that displays 3D information into the real world to enhance or augment reality. Scientists and technology practitioners think that AR can help people collaborate in a better way. The AR system needs to have a good understanding of the physical environment to support exchanging spatial information in the first place. However, limited by current technology, acquiring spatial information from the real world is not always possible or reliable.
In this dissertation, we first illustrate the severity of insufficient environmental knowledge when collaborators sit next to each other in AR. Then we present pointing ray techniques to help AR collaborators refer to distant objects without knowing where those objects are. We further explore different marking techniques that can help the AR system calculate the position of a point in space without scanning the area. Last, we provide an AR application that supports efficient spatial information communication in remote discussion around physical objects.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/110363 |
Date | 27 May 2022 |
Creators | Li, Yuan |
Contributors | Computer Science, Bowman, Douglas A., Gabbard, Joseph L., Santos Lages, Wallace, Hollerer, Tobias, Lee, Sang Won |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Dissertation |
Format | ETD, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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