Cited by 4Interactive and Immersive DisplaysHand Gesture Recognition SystemsUsability and User Interface Design

The DOI matches its Crossref record, with a small difference in title or year; 1 of the 1 references it cites were found in a registry or an index.

Evaluation of a commodity VR interaction device for gestural object manipulation in a three dimensional work environment

Abstract

Designers and engineers working in the computer-aided drafting (CAD) and computer-aided engineering (CAE) domains routinely interact with specialized computer software featuring three dimensional (3D) work environments. These professionals must manipulate virtual objects or components within this 3D work environment, but typically use traditional interaction devices with outdated technology that are more suitable for 2D work tasks. Current CAD and CAE software is designed to accommodate outdated interaction technology, but this functionality comes at the cost of efficiency in the virtual workspace. A new class of affordable interaction devices with characteristics and specifications of high-end virtual reality interaction devices is now available to consumers. These commodity VR interaction devices monitor the position and orientation of a user's hands through space to control aspects of desktop software in ways that are impossible with the traditional mouse and keyboard pair. They can be integrated with CAD or CAE software to allow gestural control of objects throughout a 3D work environment.\nTo evaluate the feasibility of gestural control for 3D work environments, a commercially available commodity VR interaction device was selected and integrated with specific 3D software. Gestures to control aspects of the software are developed and organized into a taxonomy. Select gestures are integrated with the software and evaluated against traditional interaction methods, using the Natural Goals Operators Methods Selection Rules Language (NGOMSL) concept. The evaluation results show that gestural interaction is efficient for object manipulation tasks, but a traditional keyboard or mouse is more efficient for basic tool selection tasks. Estimated learning times for each input method indicate gestural control takes about 30 seconds longer to learn than traditional interaction methods.

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Crossref · 10.31274/etd-180810-3851

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Metadata

Authors
Thompson, F. V.
Affiliations
Iowa State University (US)
Corresponding author
Thompson, Frederick Victor
Published
2014-01-01
OpenAlex
W2186517475
Cited by
4
References
1
Citations by year
2022: 1 · 2017: 2 · 2016: 1
Type
dissertation
Language
en
Open access
closed
Locations
Iowa State University Digital Repository (Iowa State University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
  • Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
Keywords
gesture-based interaction, computer-aided drafting, computer-aided engineering, object manipulation, hand tracking, gesture taxonomy, learning time, tool selection, virtual reality

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