Personalised Human Device Interaction through Context aware Augmented Reality

Abstract

Human-device interactions in smart environments are shifting prominently towards naturalistic user interactions such as gaze and gesture. However, ambiguities arise when users have to switch interactions as contexts change. This could confuse users who are accustomed to a set of conventional controls leading to system inefficiencies. My research explores how to reduce interaction ambiguity by semantically modelling user specific interactions with context, enabling personalised interactions through AR. Sensory data captured from an AR device is utilised to interpret user interactions and context which is then modeled in an extendable knowledge graph along with user's interaction preference using semantic web standards. These representations are utilized to bring semantics to AR applications about user's intent to interact with a particular device affordance. Therefore, this research aims to bring semantical modeling of personalised gesture interactions in AR/VR applications for smart/immersive environments.