Tracking with Omni-Directional Vision for Outdoor AR Systems

Most pose (3D position and 3D orientation) tracking methods using vision require a priori knowledge about the environment and correspondences between 3D environment features and 2D images. This environmental information is difficult to acquire accurately for large working volumes or may not be available at all, especially for outdoor environments. As a result, most pose tracking methods using vision are designed for small indoor working spaces. We track the pose of a moving camera from 2D images of the world. The pose of a camera is tracked through two 5 degree-of-freedom (DOF) motion estimations, which requires only 2D-to-2D correspondences. Therefore, the presented method can be applied to varied working space sizes including outdoor environments.