A context‐aware mobile augmented reality pet interaction model to enhance user experience
Yan Luo, Fang Liu, Yingying She, Baorong Yang · Computer Animation and Virtual Worlds · 2022
Abstract Virtual pet applications have been widely developed and applied in various fields. Mobile augmented reality (MAR) provides a new medium for virtual pets, allowing users to have a more immersive interactive experience through MAR pets. However, the issue of the user experience in MAR pets remains uninvestigated and relatively unexploited. Therefore, this article proposes a context‐aware MAR pet interaction model (CAPet model) to enhance the user experience in MAR pet systems, which allows the MAR pet makes feedback adaptively corresponding to the dynamic context. In addition, this article presents a user experience pyramid to measure the user experience for MAR pet. According to the proposed CAPet model, a MAR pet‐dog application is designed and implemented, based on which user test are conducted. The results of user test indicate the effectiveness of the proposed method on enhancing user experience, which provides a basis for the design of MAR pet applications in the future.