Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes

Abstract

Current Augmented Reality devices rely heavily on real-time environment mapping to provide convincing world-relative experiences through user interaction with virtual content integrated into the real world. This mapping is obtained and updated through many different algorithms, but often results in holes and other mesh artifacts when generated in less ideal scenarios, like outdoors and with fast movement. In this work, we present the Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes, a quick, interaction-triggered method to estimate the normal and position of missing mesh pieces in real-time with low computational overhead. We achieve this by extending the user's hand using a group of additional raycast sample points, aggregating results according to different algorithms, and then using the resulting values to place an object. This thesis will first cover problems with current mapping techniques, thoroughly explain the rationale and algorithms behind our method, and then evaluate our method using a user study.