Augmented reality is an old technology that is still far away from being perfect. It is also quickly being improved upon and the state of AR today has come a long way from AR just a couple of years ago. New big players have recently introduced their tools and have made it easier than ever to develop AR applications. In this study we look at what established methods (if any) there are for AR evaluation, develop AR evaluation methods that fit our needs, carry out the evaluation and analyze the collected data. We also note some important things to think about when working with AR to increase tracking and recognition stability. The recommendations are: try to have reference images with high scores, have reference objects that are distinct enough from one another to not be mixed up and make sure that the visual for the reference image matches the visual for the reference object in its intended viewing environment.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-166756 |
| Date | January 2020 |
| Creators | Lundqvist, Sebastian, Ekstrand, Oliver |
| Publisher | Linköpings universitet, Interaktiva och kognitiva system, Linköpings universitet, Interaktiva och kognitiva system |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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