A Flexible Software Architecture for Hybrid Tracking

Fusion of vision‐based and inertial pose estimation has many high‐potential applications in navigation, robotics, and augmented reality. Our research aims at the development of a fully mobile, completely self‐contained tracking system, that is able to estimate sensor motion from known 3D scene structure. This requires a highly modular and scalable software architecture for algorithm design and testing. As the main contribution of this paper, we discuss the design of our hybrid tracker and emphasize important features: scalability, code reusability, and testing facilities. In addition, we present a mobile augmented reality application, and several first experiments with a fully mobile vision‐inertial sensor head. Our hybrid tracking system is not only capable of real‐time performance, but can also be used for offline analysis of tracker performance, comparison with ground truth, and evaluation of several pose estimation and information fusion algorithms. © 2004 Wiley Periodicals, Inc.