Systems, methods, and non-transitory computer-readable media can store a set of image portions that forms an image at a specified resolution. A request for the image can be acquired from a client device. The request can include information about one or more properties associated with the client device. A subset of image portions can be selected out of the set of image portions based on the one or more properties associated with the client device. The subset of image portions can be transmitted to the client device in response to the request.

A social networking system provides a short, unbiased biographical summary for a user of the social networking system. The short biography includes a few relevant biographical information items selected from the user's profile and is displayed on the profile page. The short biography may be displayed with a set of photographs also selected from the profile for their relevance. Relevance may be based on various information including temporal relevance and relevance to the viewing user. Display of the short biography allows a viewer to easily find current biographical information about the user in an abbreviated format.

A social networking system provides a short, unbiased biographical summary for a user of the social networking system. The short biography includes a few relevant biographical information items selected from the user's profile and is displayed on the profile page. The short biography may be displayed with a set of photographs also selected from the profile for their relevance. Relevance may be based on various information including temporal relevance and relevance to the viewing user. Display of the short biography allows a viewer to easily find current biographical information about the user in an abbreviated format.

An object recognition system includes a storage device, a reading unit, an output device, and a processor. The storage device stores a dictionary containing attributes of a plurality of registered objects. The attributes includes at least a category and feature values. The reading unit includes an image capturing device. The processor registers a new object by (i) extracting a feature value of the new object from an image of the new object captured by the image capturing device, (ii) comparing the extracted feature value with feature values of registered objects that are registered in the dictionary to calculate a similarity degree therebetween, (iii) registering the extracted feature value in the dictionary as a determination criteria for an object recognition, and (iv) outputting a notification through the output device prior to the registering, upon a result of the comparing meets a predetermined condition.

An object recognition system includes a storage device, a reading unit, an output device, and a processor. The storage device stores a dictionary containing attributes of a plurality of registered objects. The attributes includes at least a category and feature values. The reading unit includes an image capturing device. The processor registers a new object by (i) extracting a feature value of the new object from an image of the new object captured by the image capturing device, (ii) comparing the extracted feature value with feature values of registered objects that are registered in the dictionary to calculate a similarity degree therebetween, (iii) registering the extracted feature value in the dictionary as a determination criteria for an object recognition, and (iv) outputting a notification through the output device prior to the registering, upon a result of the comparing meets a predetermined condition.

An electronic apparatus for providing a service associated with images is provided. The electronic apparatus includes a memory, and a processor configured to acquire multiple images, acquire information associated with at least one of the multiple images, classify at least some of the multiple images into at least one group based on the information associated with the at least one of the multiple images, and provide a service based on information of the classification of the at least some of the multiple images.

Techniques are described for an autonomous asset management system that integrates autonomous devices, such as drone devices and other robotic devices, with a home security system of a property to enable management, monitoring, and/or tracking of various assets located within the property. In some implementations, an indication of an asset associated with a property is obtained by an autonomous device. Sensor data collected by one or more sensors of the property is obtained by the autonomous device based on the indication of the asset. A present status of the asset is determined by the autonomous device based on the sensor data. A determination that the present status of the asset does not correspond to an expected status of the asset is made by the autonomous device. In response, the autonomous device navigates to the particular location of the property.

A method for location validation through physical surroundings is described. In one embodiment, the method includes receiving a location of a user device, transmitting to the user device, a request for additional information, receiving the additional information from the user device in response to the request, the second identifier matching the first identifier, comparing the received additional information with stored data pre-associated with the received location, and verifying the received location based at least in part on the comparing. In some embodiments, the request for additional information includes at least one of a request for a first image captured at a first direction, a request for a second image captured at a second direction, a request for a third image captured at a pre-determined tilt angle, a request for a stream of images captured in a pre-determined pattern, or any combination thereof.

In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.

A system and method for presenting video asset information to a viewer to assist the view in selecting a video asset for viewing. The video assets can be available from a plurality of different video asset sources, such as VOD (video on demand), PVR (personal video recorders) and broadcast (including over the air, cable, and satellite). Images from the video assets are displayed in a uniform manner, along with information about the video assets. The information includes data in a metadata category. The view can select one of the video assets for viewing, but also can navigate using metadata categories such as genre, actors, director etc. This allows a much easier and natural navigating and selection process for viewers.