A method (1400) of and a system (222) for associating past activity indications (602) associated with past activities of a user (170) with items. The method comprises accessing (1402) the past activity indications (602); accessing (1404) item indications; determining (1406) a past activity feature vector (606); determining (1408) a text feature vector (706) corresponding to the text features; mapping (1410) the past activity feature vector (606) and the text feature vector (706) to generate a text feature space (904); determining (1412) an image feature vector (806); mapping (1414) the past activity feature vector (606) and the image feature vector (806) to generate an image feature space (1004); generating a user item space (1104); and storing (1418) the user item space (1104). A method (1500) of and a system (222) for associating a first item and a second item are also disclosed.

In some examples, image based target analysis may include performing a search to identify an image, and determining whether a target is present in the image, and image metadata. Image based target analysis may further include performing, in response to a determination that the target is present in the image, based on a relationship of the target to an entity, and the image metadata, a further search to identify another image, and generating, based on the image and/or the other image, a result indicative of further information on the target.

Systems, devices, and methods for receiving image data; transferring the captured image data to a server having a processor and addressable memory via a network-connected computing device; storing the captured image data on the server; generating captured image metadata based on the stored captured image data; providing access to the captured image data and captured image metadata via an image management component; displaying, by the image management component, the captured image data; and filtering, by the image management component, the captured image data based on the generated captured image metadata.

Systems, devices, and methods for receiving image data; transferring the captured image data to a server having a processor and addressable memory via a network-connected computing device; storing the captured image data on the server; generating captured image metadata based on the stored captured image data; providing access to the captured image data and captured image metadata via an image management component; displaying, by the image management component, the captured image data; and filtering, by the image management component, the captured image data based on the generated captured image metadata.

Provided are techniques for enhancing images with emotion information, comprising capturing a plurality of images; identifying an individual in the plurality of images; analyzing the plurality of images for emotional content; converting the emotional content into emotion metadata; correlating the emotional content with the individual to produce associated emotion metadata; and storing the associated emotion metadata in conjunction with the captured image in a computer-readable storage medium. The disclosed techniques may also include capturing physiological data corresponding to an individual that captures the image; analyzing the physiological data for a second emotional content; converting the second emotional content into a second emotion metadata; storing the second emotion metadata in conjunction with the captured image in the computer-readable storage medium.

The present disclosure relates to providing a multi-user computer generated reality (“CGR”) session. In some embodiments, a first electronic device displays a CGR environment, wherein the CGR environment is responsive to input from the first electronic device and a second electronic device, wherein the second device is external to the first device. While displaying the CGR environment, the device obtains a first scene graph from a process executing on the first device, wherein the first scene graph includes information for rendering a first entity, and obtains a second scene graph from a process executing on the second device, wherein the second scene graph includes information for rendering a second entity. The first electronic device updates the displayed CGR environment based on the first scene graph and the second scene graph, wherein the displayed CGR environment includes a visual representation of the first and a visual representation of the second entity.

Information relating to a subset of images within a set of images is received. The information includes metadata of each image. The subset of images are selected from the set of images based upon each image in the subset of images being acquired within a bounding area surrounding a geographical position of a current image. Weight information is received. The weight information controls weights to be given to a plurality of different measures of similarities. A plurality of combined measures of similarity for pairs of images in the subset of images are calculated.

Concepts and technologies directed to surrogate metadata aggregation for dynamic content assembly are disclosed. Embodiments can include a system that comprises a processor and a memory that stores computer-executable instructions that configure a processor to perform operations. The operations can include obtaining a first visual content from a digital data store, where the first visual content is configured to digitally represent a first scene. The operations can include performing image recognition on the first visual content so as to identify a second visual content that is digitally configured to represent a second scene. The operations can include determining that native original metadata cannot be obtained for the first visual content, where the native original metadata includes information about the first scene digitally represented by the first visual content. The operation can include generating surrogate metadata for the first visual content based on metadata obtained from the second visual content.

A system and method for managing inventories of orthopaedic implants includes receiving a medical image of a bone of a patient from a healthcare provider, performing a digital templating procedure on the medical image to determine an orthopaedic implant for use with the bone of the patient; transmitting the digital templated medical image to the healthcare provider, and shipping the orthopaedic implant to the healthcare provider in response to an electronic approval of the digital templated medical image received from the healthcare provider. Implant constraint data may also be received from the healthcare provider and used in determining the orthopaedic implant. In addition, a number of orthopaedic implants having a range of different sizes based on the size of the determined orthopaedic implant may be shipped to the healthcare provider. In some embodiments, the healthcare provider may perform the digital templating procedure on the medical image.

Systems and methods are disclosed herein for determining placement of Augmented Reality (AR) content. In some embodiments, a processor detects input at a first client device of a first user that a transportation session between the first user and a second user has begun. In response to detecting the input, the processor determines a first location of the first client device based on an image captured by the first client device, and determines a geospatial offset of a second client device of the second user from the first client device. The processor determines a second location of the second client device based on the first location of the first client device and the geospatial offset, and generates for display by the second client device AR content, the AR content being selected based on an orientation of the second client device and the second location.