Author: Supun Samarasekera

This paper proposes a novel vision-aided navigation approach that continuously estimates precise 3D absolute pose for aerial vehicles, using only inertial measurements and monocular camera observations.

The system combines a wearable Optical-See-Through (OST) display device with high precision 6-Degree-Of-Freedom (DOF) pose tracking and a virtual personal assistant (VPA) with natural language, verbal conversational interaction, providing guidance to the user in the form of visual, audio and locational cues.

In this paper we present an augmented reality binocular system to allow long range high precision augmentation of live telescopic imagery with aerial and terrain based synthetic objects, vehicles, people and effects.

This paper proposes a navigation algorithm that provides a low-latency solution while estimating the full nonlinear navigation state.

We present an augmented reality system based on Kinect for on-line handbag shopping. The users can virtually try on different handbags on a TV screen at home.

Stereo Vision processing is a critical component of Augmented Reality systems that rely on the precise depth map of a scene to properly place computer generated objects with real life video.

In this paper, we demonstrated that with the use of precise 3D Li-dar range data, we are able to build a global consistent database of high precision 3D visual landmarks, which improves the landmark matching accuracy dramatically.