Hybrid tracking system for robust fiducials registration in augmented reality

Abstract

An effective augmented reality system requires an accurate registration of virtual graphics on real images. In this work, we developed a multi-modal tracking architecture for object identification and occlusion handling. Our approach combines several sensors and techniques to overcome the environment changes. This architecture is composed of a first coded targets registration module based on a hybrid algorithm of pose estimation. To manage partial target occlusions, a second module based on a robust method for feature points tracking is developed. The latest component of the system is the hybrid tracking module. This multi-sensors part handles total target occlusions issue. Experiments with the multi-modal system proved the effectiveness of the proposed tracking approach and occlusion handling in augmented reality applications.