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Virginia Tech

Walk-Centric User Interfaces for Mixed Reality

Abstract

dc:description.abstract

Walking is a natural part of our lives and is also becoming increasingly common in mixed reality. Wireless headsets and improved tracking systems allow us to easily navigate real and virtual environments by walking. In spite of the benefits, walking brings challenges to the design of new systems. In particular, designers must be aware of cognitive and motor requirements so that walking does not negatively impact the main task. Unfortunately, those demands are not yet fully understood. In this dissertation, we present new scientific evidence, interaction designs, and analysis of the role of walking in different mixed reality applications. We evaluated the difference in performance of users walking vs. manipulating a dataset during visual analysis. This is an important task, since virtual reality is increasingly being used as a way to make sense of progressively complex datasets. Our findings indicate that neither option is absolutely better: the optimal design choice should consider both user's experience with controllers and user's inherent spatial ability. Participants with reasonable game experience and low spatial ability performed better using the manipulation technique. However, we found that walking can still enable higher performance for participants with low spatial ability and without significant game experience. In augmented reality, specifying points in space is an essential step to create content that is registered with the world. However, this task can be challenging when information about the depth or geometry of the target is not available. We evaluated different augmented reality techniques for point marking that do not rely on any model of the environment. We found that triangulation by physically walking between points provides higher accuracy than purely perceptual methods. However, precision may be affected by head pointing tremors. To increase the precision, we designed a new technique that uses multiple samples to obtain a better estimate of the target position. This technique can also be used to mark points while walking. The effectiveness of this approach was demonstrated with a controlled augmented reality simulation and actual outdoor tests. Moving into the future, augmented reality will eventually replace our mobile devices as the main method of accessing information. Nonetheless, to achieve its full potential, augmented reality interfaces must support the fluid way we move in the world. We investigated the potential of adaptation in achieving this goal. We conceived and implemented an adaptive workspace system, based in the study of the design space and through user contextual studies. Our final design consists in a minimum set of techniques to support mobility and integration with the real world. We also identified a set of key interaction patterns and desirable properties of adaptation-based techniques, which can be used to guide the design of the next-generation walking-centered workspaces.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Santos Lages, Wallace
Chair dc:contributor.committeechair
  • Bowman, Douglas A.
Committee members dc:contributor.committeemember
  • Hollerer, Tobias
  • Gabbard, Joseph L.
  • Polys, Nicholas F.
  • North, Christopher L.

Subjects

dc:subject × 7

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:16715
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/84460

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Santos Lages, Wallace. Walk-Centric User Interfaces for Mixed Reality. doctoral thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/84460