GPS Refinement and Camera Orientation Estimation from a Single Image and a 2D Map

Hang Chu, Andrew Gallagher, Tsuhan Chen; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2014, pp. 171-178

A framework is presented for refining GPS location and estimate the camera orientation using a single urban building image, a 2D city map with building outlines, given a noisy GPS location. We propose to use tilt-invariant vertical building corner edges extracted from the building image. A location-orientation hypothesis, which we call an LOH, is a proposed map location from which an image of building corners would occur at the observed positions of corner edges in the photo. The noisy GPS location is refined and orientation is estimated using the computed LOHs. Experiments show the framework improves GPS accuracy significantly, generally produces reliable orientation estimation, and is computationally efficient.