Semi-automatic Annotations in Unknown Environments

Unknown environments pose a particular challenge for augmented reality applications because the 3D models required for tracking, rendering and interaction are not available ahead of time. Consequently, authoring of AR content must take place on-line. This work describes a set of techniques to simplify the online authoring of annotations in unknown environments using a simultaneous localisation and mapping (SLAM) system. The point-based SLAM system is extended to specifically track and estimate high-level features indicated by the user. The automatic estimation of these complex landmarks by the system relieves the user from the burden of manually specifying the full 3D pose of annotations while improving accuracy. These properties are especially interesting for remote collaboration applications where either user interfaces on handhelds or camera control by the remote expert are limited.