A hybrid and linear registration method utilizing inclination constraint

This work describes a new hybrid vision-based registration method with an inclination sensor. In the method, a camera is tracked by solving linear equations under inclination constraint. Linear operations are faster than the nonlinear optimization process, but the output does not usually satisfy the orthonormality constraint. On the contrary, the proposed method calculates the camera position and azimuth directly, thus the result satisfies the orthonormality constraint. Many hybrid approaches using inertia sensors have been proposed for AR/MR. However, such methods still depend on vision-based methods in initialization processes. On the other hand, the proposed method is totally hybrid in that the inclination measured by the sensor is always incorporated in pose calculation process as well as vision information. The method can be used in initialization process of conventional hybrid methods as well as it can be used as an independent registration method. The proposed method can be applied to not only inside-out-style camera tracking but also outside-in-style object tracking.