A Markerless Augmented Reality System for Mobile Devices

Augmented Reality (AR) combines a live view of a real world environment with computer-generated virtual content. An AR system poses unique challenges including requiring a high quality camera pose estimate and operating on resource-limited platforms. We present a full system based on a hybrid approach using ORB binary features and optic flow that is able to run on a consumer tablet device in near real time. The system uses an adaptive map of features designed to extend the usable range possible with ORB features. We demonstrate how real time performance is possible with platform specific optimizations, and propose the use of two different existing pose estimation algorithms to further improve speed and extend the usable tracking range.