Never Get Lost Again: Vision Based Navigation Using StreetView Images

Aparna Taneja, Luca Ballan, Marc Pollefeys

Abstract: In this paper we propose a simple and lightweight solution to estimate the geospatial trajectory of a moving vehicle from images captured by a cellphone exploiting the map and the imagery provided by Google Streetview. Images are intelligently compared against the streetview data, and a recursive Bayesian framework is applied to perform continuous localization of the vehicle inside the discrete structure of the streetview graph. Experiments run on a dataset $$10.7$$  km long, show that the system is able to infer its position and orientation despite the low resolution and limited field of view offered by an off the shelf consumer device. Our method shows to be robust with respect to significant changes in appearance and structure of the environment across the images, obtaining an average accuracy of $$13$$  m in position, and $$16^\circ $$ in orientation.