Vehicle localization

A computer, comprising:

• a processor;
• and
• a memory, the memory including instructions executable by the processor to:
• determine an approximate camera location on a route by inputting a first image acquired by a camera included in a vehicle to a convolutional neural network;
• extract first image feature points from the first image;
• select pose estimation parameters for a pose estimation algorithm based on the approximate camera location;
• determine a six degree-of-freedom (DoF) camera pose by inputting the first image feature points and second feature points included in a structure-from-motion (SfM) map based on the route to the pose estimation algorithm which is controlled by the pose estimation parameters, wherein the SfM map includes a collection of three-dimensional points visible from the route generated by determining three-dimensional locations of image feature points in global coordinates from the dataset of reference images and combining them using a 3D mapping software program;
• and
• determine a six DoF vehicle pose based on the six DoF camera pose.