A method of determining a pose of an image capture device 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. Moreover, the method includes reading metadata corresponding to the most similar known data structure to determine a pose of the image capture device.

A method of determining a pose of an image capture device 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. Moreover, the method includes reading metadata corresponding to the most similar known data structure to determine a pose of the image capture device.

A wearable apparatus is provided for capturing and processing images from an environment of a user. In one implementation, a wearable apparatus includes a transmitter, a memory, an image sensor configured to capture a stream of images from an environment of a user of the wearable apparatus, and a processing device. The processing device is programmed to receive the stream of images from the image sensor, analyze the stream of images to detect the external device in the environment of the user, and cause the transmitter to transmit an interrogation signal that is configured to cause a change in an aspect of the external device. The processing device is further programmed to analyze the stream of images to detect the change in the aspect of the external device and, after detection of the change, store in the memory information relating to the external device.

A system, method and computer program product for accessing content based on an image. The method comprises comparing an image to a database of images, each of the images of the database being associated with at least one corresponding audio track, identifying those ones images of the database that correspond to the image, and identifying the at least one corresponding audio track that corresponds to the identified images. In one example aspect, the method also comprises presenting the audio track to a user. Corresponding metadata also can be presented. The images may be classified by, e.g., genre, musical album, concept, or the like, and, in cases where an input image is determined to belong to any such classes, audio content and/or metadata relating thereto are identified and presented to the user.

This application provides an image classification method and an electronic device. The image classification method includes: detecting, by a first electronic device, a connection to a second electronic device; allowing, by the first electronic device, a data access request of the second electronic device; sending, by the second electronic device, request information to the first electronic device, where the request information is used to request information about an image in one or more image sets, and each of the one or more image sets is obtained by the first electronic device by classifying images shot by a camera of the first electronic device; sending, by the first electronic device, response information to the second electronic device; and displaying, by the second electronic device, information about each image set by using a display.

This application provides an image classification method and an electronic device. The image classification method includes: detecting, by a first electronic device, a connection to a second electronic device; allowing, by the first electronic device, a data access request of the second electronic device; sending, by the second electronic device, request information to the first electronic device, where the request information is used to request information about an image in one or more image sets, and each of the one or more image sets is obtained by the first electronic device by classifying images shot by a camera of the first electronic device; sending, by the first electronic device, response information to the second electronic device; and displaying, by the second electronic device, information about each image set by using a display.

A computer-implemented method for automatically detecting events and creating photo-product designs based on the events in a photo-product design system includes automatically identifying an event by an event detection module based on daily numbers of captured photos over a plurality of days, automatically selecting a photo-product type by an intelligent product design creation engine in the photo-product design system, calculating a daily weight for a photo product design in the photo-product type based on the daily numbers of captured photos, automatically determining a number of product photos allocated to each day based on associated daily weight, automatically selecting product photos from the captured photos each day at the event according to the number of product photos allocated to each day, and automatically creating a photo-product design for the event using the selected product photos.

Techniques for generating an arbitrary view of an asset are disclosed. In some embodiments, arbitrary view generation includes storing a set of images associated with an asset in a database and generating an image comprising a requested view of the asset using at least a subset of the set of images associated with the asset that are stored in the database.

Techniques for generating an arbitrary view of an asset are disclosed. In some embodiments, arbitrary view generation includes storing a set of images associated with an asset in a database and generating an image comprising a requested view of the asset using at least a subset of the set of images associated with the asset that are stored in the database.

Techniques for machine learning based image attribute determination are disclosed. In some embodiments, one or more unknown attributes of a received image comprising a prescribed environment are determined using a machine learning based framework. The machine learning based framework is at least in part trained on image data sets comprising a model environment that substantially simulates the prescribed environment.