Abstract: An image localization system is described. A server stores a localization model that associates location and orientation data with each picture among a plurality of pictures. The server receives a query for a location and an orientation of a device. The query includes a first picture. A second picture that matches the first picture is identified. The server determines the location and the orientation of the device based on the location and orientation data corresponding to the second picture. The location and orientation data indicates position, orientation, three-dimensional geometry, gyroscope measurement, and accelerometer measurement.

Abstract: A device for multi-spectrum segmentation for computer vision is described. A first optical sensor operates within a first spectrum range and generates first image data corresponding to a first image captured by the first optical sensor. A second optical sensor operates within a second spectrum range different from the first spectrum range and generates second image data corresponding to a second image captured by the second optical sensor. The device identifies a first region in the first image, maps a first portion of the first image to a second portion of the second image data, provides the second portion of the second image data to a server that generates augmented reality content based on the second portion of the second image data. The device displays the augmented reality content.

Abstract: An image localization system is described. A server stores a localization model that associates location and orientation data with each picture among a plurality of pictures. The server receives a query for a location and an orientation of a device. The query includes a first picture. A second picture that matches the first picture is identified. The server determines the location and the orientation of the device based on the location and orientation data corresponding to the second picture. The location and orientation data indicates position, orientation, three-dimensional geometry, gyroscope measurement, and accelerometer measurement.

Abstract: A device for multi-spectrum segmentation for computer vision is described. A first optical sensor operates within a first spectrum range and generates first image data corresponding to a first image captured by the first optical sensor. A second optical sensor operates within a second spectrum range different from the first spectrum range and generates second image data corresponding to a second image captured by the second optical sensor. The device identifies a first region in the first image, maps a first portion of the first image to a second portion of the second image data, provides the second portion of the second image data to a server that generates augmented reality content based on the second portion of the second image data. The device displays the augmented reality content.

Abstract: An image localization system is described. A receiver receives visual inertial navigation (VIN) data and corresponding image data from devices, the VIN data indicating VIN states and corresponding poses of the devices. A training module generates a localization model based on the VIN data and corresponding image data from the plurality of devices. The image data includes images, the localization model correlating the VIN states and poses with each image among the plurality of images. An image localizer receives a query for a geographic location and a pose of a device. The query includes a picture. The image localizer compares the picture with images from the localization model, identifies an image based on the localization model, the image matching the picture in the query, and determines the geographic location and the pose of the device based on the VIN state and pose corresponding to the identified image.

Abstract: A system and method for multi-spectrum segmentation for computer vision is described. A first sensor captures an image within a first spectrum range and generates first sensor data. A second sensor captures an image within a second spectrum range different than the first spectrum range and generates second sensor data. A multi-spectrum segmentation module identifies a segmented portion of the image within the second spectrum range based on: the second sensor data, a subset of the first sensor data corresponding to the segmented portion of the image within the second spectrum range, and a segmented portion of the image at the second spectrum range corresponding to the subset of the first sensor data. The multi-spectrum segmentation module identifies a physical object in the segmented portion of the image within the second spectrum range, and a device generates augmented reality content based on the identified physical object.

Abstract: An image localization system is described. A receiver receives visual inertial navigation (VIN) data and corresponding image data from devices, the VIN data indicating VIN states and corresponding poses of the devices. A training module generates a localization model based on the VIN data and corresponding image data from the plurality of devices. The image data includes images, the localization model correlating the VIN states and poses with each image among the plurality of images. An image localizer receives a query for a geographic location and a pose of a device. The query includes a picture. The image localizer compares the picture with images from the localization model, identifies an image based on the localization model, the image matching the picture in the query, and determines the geographic location and the pose of the device based on the VIN state and pose corresponding to the identified image.

Abstract: A system and method for multi-spectrum segmentation for computer vision is described. A first sensor captures an image within a first spectrum range and generates first sensor data. A second sensor captures an image within a second spectrum range different than the first spectrum range and generates second sensor data. A multi-spectrum segmentation module identifies a segmented portion of the image within the second spectrum range based on: the second sensor data, a subset of the first sensor data corresponding to the segmented portion of the image within the second spectrum range, and a segmented portion of the image at the second spectrum range corresponding to the subset of the first sensor data. The multi-spectrum segmentation module identifies a physical object in the segmented portion of the image within the second spectrum range, and a device generates augmented reality content based on the identified physical object.