Next generation driver assistance systems require precise self localization. Common approaches using global navigation satellite systems (GNSSs) suffer from multipath and shadowing effects often rendering this solution insufficient. In urban environments this problem becomes even more pronounced. Herein we present a system for six degrees of freedom (DOF) ego localization using a mono camera and an inertial measurement unit (IMU). The camera image is processed to yield a rough position estimate using a previously computed landmark map. Thereafter IMU measurements are fused with the position estimate for a refined localization update. Moreover, we present the mapping pipeline required for the creation of landmark maps. Finally, we present experiments on real world data. The accuracy of the system is evaluated by computing two independent ego positions of the same trajectory from two distinct cameras and investigating these estimates for consistency. A mean localization accuracy of 10 cm is achieved on a 10 km sequence in an inner city scenario.