Relocalization systems and methods

The present disclosure relates to the localisation of pose-sensitive systems. One disclosed embodiment relates to a method of determining a pose of an image capture device. The method includes capturing an image using an image capture device. The method also includes generating a data structure corresponding to the captured image. The method further includes comparing the data structure with a plurality of known data structures to identify a most similar known data structure. The method further includes reading metadata corresponding to the most similar known data structure to determine a pose of the image capture device. The method further includes training a neural network by mapping a plurality of known images to the plurality of known data structures. The data structure is an N dimensional vector. The step of generating the data structure corresponding to the captured image comprises using a neural network to map the captured image to the N dimensional vector. Each known image of the plurality has respective metadata including pose data. The step of training the neural network comprises accessing a database of the known images annotated with the respective metadata, decreasing a first Euclidean distance between first and second known N dimensional vectors respectively corresponding to matching first and second known images in an N dimensional space, and increasing a second Euclidean distance between first and third known N dimensional vectors respectively corresponding to non-matching first and third known images in the N dimensional space.