Satellite Images Help Track a Vehicle

Researchers from the Toyota Technological Institute at Chicago (TTIC) and Carnegie Mellon University developed a deep learning-based method that locates a ground vehicle by using satellite imagery as the only prior knowledge of the environment.
Knowing the exact location of a vehicle is critical for autonomous cars, and currently GPS systems are being used which the researchers claim suffer from limited precision and are sensitive to multipath effects – such as in “urban canyons” formed by tall buildings.
Using TITAN X GPUs, CUDA, and Keras with the Theano deep learning framework, the researchers multi-view neural network learns to match ground-level images with their corresponding satellite view. For training, they used ground-level images from the KITTI dataset collected from a moving vehicle and paired them with the matching satellite image.