LevelEd VR: A virtual reality level editor and workflow for virtual reality level design
AffiliationUniversity of Chester
MetadataShow full item record
AbstractVirtual reality entertainment and serious games popularity has continued to rise but the processes for level design for VR games has not been adequately researched. Our paper contributes LevelEd VR; a generic runtime virtual reality level editor that supports the level design workflow used by developers and can potentially support user generated content. We evaluated our LevelEd VR application and compared it to an existing workflow of Unity on a desktop. Our current research indicates that users are accepting of such a system, and it has the potential to be preferred over existing workflows for VR level design. We found that the primary benefit of our system is an improved sense of scale and perspective when creating the geometry and implementing gameplay. The paper also contributes some best practices and lessons learned from creating a complex virtual reality tool, such as LevelEd VR.
CitationBeever, L., Pop, S. W. & John, N, W. (2020). LevelEd VR: A virtual reality level editor and workflow for virtual reality level design. 2020 IEEE Conference on Games (24-27th August). 10.1109/CoG47356.2020.9231769
PublisherIEEE Conference Publications
JournalIEEE Conference on Games
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Except where otherwise noted, this item's license is described as Attribution-ShareAlike 4.0 International
Showing items related by title, author, creator and subject.
Evaluating LevelEd AR: An Indoor Modelling Application for Serious Games Level DesignBeever, Lee; Pop, Serban R.; John, Nigel W.; University of Chester (IEEE Conference Publications, 2019-09-06)We developed an application that makes indoor modelling accessible by utilizing consumer grade technology in the form of Apple’s ARKit and a smartphone to assist with serious games level design. We compared our system to that of a tape measure and a system based on an infra-red depth sensor and application. We evaluated the accuracy and efficiency of each system over four different measuring tasks of increasing complexity. Our results suggest that our application is more accurate than the depth sensor system and as accurate and more time efficient as the tape measure over several tasks. Participants also showed a preference to our LevelEd AR application over the depth sensor system regarding usability.
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