Fusion of vision and gyro tracking for robust augmented reality registration

A novel framework enables accurate augmented reality (AR) registration with integrated inertial gyroscope and vision tracking technologies. The framework includes a two-channel complementary motion filter that combines the low-frequency stability of vision sensors with the high-frequency tracking of gyroscope sensors, hence achieving stable static and dynamic six-degree-of-freedom pose tracking. Our implementation uses an extended Kalman filter (EKF). Quantitative analysis and experimental results show that the fusion method achieves dramatic improvements in tracking stability and robustness over either sensor alone. We also demonstrate a new fiducial design and detection system in our example AR annotation systems that illustrate the behavior and benefits of the new tracking method.