Deep Image Localization

A computer-implemented method comprising:

• receiving visual inertial navigation (VIN) data and corresponding image data from a plurality of devices, the VIN data indicating VIN states and corresponding poses of the plurality of devices;
• generating a localization model based on the VIN data and corresponding image data from the plurality of devices, the image data including a plurality of images, the localization model correlating the VIN states and poses with each image among the plurality of images;
• receiving a query for a geographic location and a pose of a device, the query including a picture;
• comparing the picture with images from the localization model;
• identifying an image based on the localization model, the image matching the picture in the query;
• and
• determining the geographic location and the pose of the device based on the VIN state and pose corresponding to the identified image.

A non-transitory machine-readable storage medium, tangibly embodying a set of instructions that, when executed by at least one processor, causes the at least one processor to perform a set of operations comprising:

• receiving visual inertial navigation (VIN) data and corresponding image data from a plurality of devices, the VIN data indicating VIN states and corresponding poses of the plurality of devices;
• generating a localization model based on the VIN data and corresponding image data from the plurality of devices, the image data including a plurality of images, the localization model correlating the VIN states and poses with each image among the plurality of images;
• receiving a query for a geographic location and a pose of a device, the query including a picture;
• comparing the picture with images from the localization model;
• identifying an image based on the localization model, the image matching the picture in the query;
• and
• determining the geographic location and the pose of the device based on the VIN state and pose corresponding to the identified image.