A method for determining a value of an item includes receiving an image of a first item captured as a result of focusing an augmented reality (AR) device on the first item. The image of the first item is compared with images of one or more second items from a database. An image of one of the second items is identified that closely corresponds to the image of the first item. Metadata is obtained for the one of the second items. Using the metadata, value information is obtained for the first item. The value information is permitted to be displayed on the AR device.

The present disclosure relates to a method and an apparatus for generating a three-dimensional model, a device, and a storage medium. The method includes: a scanned texture image and a depth image corresponding to the texture image are acquired; the texture image is processed by a pre-trained mask region convolutional neural network to determine at least one region of interest on the texture image and category information and mask information of each of the at least one region of interest; the depth image is updated according to the category information and the mask information of each of the at least one region of interest to obtain a updated depth image; and a three-dimensional model corresponding to the updated depth image is constructed.

The disclosure relates to systems and methods for vessel image analysis. The method includes receiving a set of images along a vessel acquired by a medical imaging device, and determining a sequence of centerline points along the vessel and a sequence of image patches at the respective centerline points based on the set of images. The method further includes detecting plaques based on the sequence of image patches using a first learning network. The first learning network includes an encoder configured to extract feature maps based on the sequence of image patches and a plaque range generator configured to generate a start position and an end position of each plaque based on the extracted feature maps. The method also includes classifying each detected plaque and determining a stenosis degree for the detected plaque, using a second learning network reusing at least part of the parameters of the first learning network and the extracted feature maps.

A method for providing virtual contents in a virtual space based on a common coordinate system includes: detecting a base marker for identifying a fixed point of an actual operation space, and a target marker for identifying an actual operation object, from initial image data indicating an initial state of the actual operation object in the actual operation space; calculating an initial model matrix of a target marker expressing an initial position and orientation of the target marker, and a model matrix of the base marker expressing a position and an orientation of the detected base marker in a virtual operation space having a common coordinate system which has the detected base marker as a reference; and calculating a current model matrix of the target marker expressing a current position and orientation of the target marker by using the calculated model matrix of the base marker.

Embodiments of the present systems and methods may provide techniques for analyzing rodent gait that addresses the confound of interdependency of gait variables to provide more accurate and reproducible results. In embodiments, multidimensional analysis of gait in animals, such as rodents, may be performed. For example, in an embodiment, a computer-implemented method of animal gait analysis may comprise capturing data relating to steps taken a plurality of animal test subjects, performing a multidimensional analysis of the captured data to generate data describing a gait of the animal test subjects, and outputting data characterizing the gait of the animal test subjects.

Provided is an information processing apparatus including a shape information acquisition part configured to acquire three-dimensional shape data on a first article possessed by a user, a degree of similarity calculation part configured to calculate, by comparing the three-dimensional shape data on the first article with three-dimensional shape data on a plurality of second articles pre-stored in a database managed by an electronic commerce business operator, a degree of similarity between the first article and each of the second articles, a selection part configured to select the second article to be recommended to the user based on each of the degrees of similarity, and an output part configured to output, to the user, information on the second article selected.

Systems and methods are disclosed for generating a 3D computer model of an eyewear product, using a computer system, the method including obtaining an inventory comprising a plurality of product frames; scanning a user's anatomy; extracting measurements of the user's anatomy; obtaining a first model of a contour and/or surface of the user's anatomy, based on the extracted measurements of the user's anatomy; identifying, based on the contour and/or the surface of the user's anatomy, a first product frame among the plurality of product frames; determining adjustments to the first product frame based on the contour and/or the surface of the user's anatomy; generating a second model rendering comprising the adjusted first product frame matching the contours and/or the surface of the user's anatomy.

Comprehensive 2D learning images are collected for learning subjects. Standardized 2D gallery images of many gallery subjects are collected, one per gallery subject. A 2D query image of a query subject is collected, of arbitrary viewing aspect, illumination, etc. 3D learning models, 3D gallery models, and a 3D query model are determined from the learning, gallery, and query images. A transform is determined for the selected learning model and each gallery model that yields or approximates the query image. The transform is at least partly 3D, such as 3D illumination transfer or 3D orientation alignment. The transform is applied to each gallery model so that the transformed gallery models more closely resemble the query model. 2D transformed gallery images are produced from the transformed gallery models, and are compared against the 2D query image to identify whether the query subject is also any of the gallery subjects.

An acquisition kit, including: a mouthpiece intended for being placed into the mouth of a patient and including a reference mark; and an image-acquisition apparatus including a screen for viewing an image that can be acquired, computer memory containing information on target acquisition conditions, and a computer program comprising program code instructions for displaying on said screen a reference in a position such that, when the reference mark matches the reference on the screen, the acquisition apparatus complies with the target acquisition conditions.

A method for hand pose identification in an automated system includes providing depth map data of a hand of a user to a first neural network trained to classify features corresponding to a joint angle of a wrist in the hand to generate a first plurality of activation features and performing a first search in a predetermined plurality of activation features stored in a database in the memory to identify a first plurality of hand pose parameters for the wrist associated with predetermined activation features in the database that are nearest neighbors to the first plurality of activation features. The method further includes generating a hand pose model corresponding to the hand of the user based on the first plurality of hand pose parameters and performing an operation in the automated system in response to input from the user based on the hand pose model.