• Assisting Serious Games Level Design with an Augmented Reality Application and Workflow

      Beever, Lee; John, Nigel W.; Pop, Serban R.; University of Chester (Eurographics Proceedings, 2019-09-13)
      With the rise in popularity of serious games there is an increasing demand for virtual environments based on real-world locations. Emergency evacuation or fire safety training are prime examples of serious games that would benefit from accurate location depiction together with any application involving personal space. However, creating digital indoor models of real-world spaces is a difficult task and the results obtained by applying current techniques are often not suitable for use in real-time virtual environments. To address this problem, we have developed an application called LevelEd AR that makes indoor modelling accessible by utilizing consumer grade technology in the form of Apple’s ARKit and a smartphone. 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. Finally, we carried out a preliminary case study that demonstrates how LevelEd AR can be successfully used as part of current industry workflows for serious games level design.
    • Evaluating LevelEd AR: An Indoor Modelling Application for Serious Games Level Design

      Beever, 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.