How does it work?
We have applied deep convolutional neural networks to camera pose regression. Our system is simple in the fact that we train a system end-to-end to regress camera pose. Unlike other systems ours does not require a large database or landmarks. Instead, it learns robust high level features. It can deal with many different camera types, motion blur, weather, pedestrians and other distractions. It is highly scalable, requiring only 50 MB of memory, and 5ms per image, to relocalise within large urban scenes.
The video to the right shows a technical summary of the system.