3DOF tracking accuracy improvement for outdoor Augmented Reality

Abstract

Outdoor Augmented Reality (AR) gained popularity recently due to its potential for location based mobile services. However, most commercially available Global Positioning Systems (GPS), except for the expensive high-end models, do not provide accurate location information that is enough to be used for displaying practically meaningful location based information. In this paper, we present a computer vision based method for improving user's two dimensional location and one-dimensional orientation, the initial values of which are obtained from a GPS and a digital compass. Our method utilizes corner positions of buildings in the map and the vertical edges of the buildings in the captured images. We applied anisotropic diffusion in order to filter noise and preserve edges, and dual vertical edge filters on gray and saturation images. Our method is suitable for mobile services in urban environments where tall buildings degrade GPS signals. In average, our method improved 15.0 meters in position and 2.2 degrees in orientation.