An electronic device is provided with a detecting unit for detecting a face and an eye from an image; an obtaining unit for obtaining a position designated by a user on a display screen on which the image is displayed; a setting unit for setting a left region for selecting a left eye of a face specified by the position designated and a right region for selecting a right eye of the face; and a selecting unit for selecting an eye region of a corresponding eye when the position designated is present in the left region or the right region. The setting unit extends a region for selecting, out of eyes of the specified face, an eye closer to an edge of the specified face when a predetermined condition is satisfied.

A dental device tracking method including acquiring, using an imager of a dental device, at least a first image which includes an image of at least one user body portion outside of a user’s oral cavity; identifying the at least one user body portion in the first image; and determining, using the at least the first image, a position of the dental device with respect to the at least one user body portion.

Provided are a method and a device for restoring a facial image, capable of restoring an image naturally by detecting positions of landmarks of a face in a bounding-box detected from an input image, improving an image using a learning model learned from a front facial image after performing warping for aligning a front face to be positioned at a central position or a reference position on the basis of the landmarks, performing inverse warping for rotating the improved image in an original direction or at an original angle, and inserting the inversely-warped image into the input image. In addition, provided are a method and a device for restoring a facial image, capable of performing pose estimation for a face in a bounding-box detected from an input image, and improving the image using a learning model learned from a side facial image corresponding to a result of the pose estimation.

Disclosed are methods, systems and apparatuses for creating an animal-shaped avatar using a human face. An avatar creation method according to example embodiments includes analyzing an image including a human face and automatically creating an animal-shaped avatar corresponding to the human face.

Aspects of the disclosure can provide method for identifying a face where multiple images to be identified are received. Each of the multiple images includes a face image part. Each face image of face images in the multiple images to be identified is extracted. An initial figure identification result of identifying a figure in the each face image is determined by matching a face in the each face image respectively to a face in a target image in an image identification library. The face images are grouped. A target figure identification result for each face image in each group is determined according to the initial figure identification result for the each face image in the each group.

A non-transitory computer-readable recording medium stores a calculation program for causing a computer to execute processing including: acquiring a captured image that includes a face; determining an occurrence state of a movement of a facial muscle, based on the captured image; and calculating a matching degree between the face and a specific fashion style, based on the occurrence state of the movement of the facial muscle.

Systems and methods for learning and recognizing features of an image are provided. A point detector identifies points in an image where there are two-dimensional changes. A geometric feature evaluator overlays at least one mesh on the image and analyzes geometric features on the at least one mesh. An internal calibrator transforms data from the point detector and the geometric feature evaluator into a three-dimensional point figure of the image, and a depth evaluator determines a final shape of the image. A three-dimensional object model of the image is constructed. The image could be a human face or body. An artificial intelligence unit learns and identifies a user's facial features including skull size, distance between eyes, and bone structure and body features including skeleton shape and body size. Exemplary systems and methods can construct and learn features of a human face based on a partial view where part of the face is covered. Systems and methods can unlock a mobile device based on recognition of the features of the user's face.

This application discloses a face image processing method performed by an electronic device. The method includes: acquiring a face image of a source face and a face template image of a template face; performing three-dimensional face modeling on the face image and the face template image to obtain a three-dimensional face image feature of the face image and a three-dimensional face template image feature of the face template image; fusing the three-dimensional face image feature and the three-dimensional face template image feature to obtain a three-dimensional fusion feature; performing face replacement feature extraction on the face image based on the face template image to obtain an initial face replacement feature; transforming the initial face replacement feature based on the three-dimensional fusion feature to obtain a target face replacement feature; and replacing the template face with the source face based on the target face replacement feature to obtain a target face image.

Disclosed herein is an apparatus comprising a camera and a processing unit operatively coupled to the camera, wherein the processing unit is configured to: receive a sequence of images captured by the camera; process a first image of the received sequence of images to compute respective likelihoods of each of a plurality of predetermined facial features being visible in the first image; compute, from the computed likelihoods, a probability that the first image depicts a predetermined first side of a human head; responsive to at least the computed probability exceeding the predetermined detection probability, trigger performance of a predetermined action.

Apparatus and methods automate selection of patient interface(s). Image data captured by an image sensor may contain facial feature(s) of a user. The facial features may be captured in association with a predetermined reference feature of known dimension(s) such as with a user interface display that is generated with a sequence of icons that are activated for directing and tracking movement within the interface for desired image capture. The user's facial feature(s) and the reference feature may be detected in the captured image data. The image may be processed to measure an aspect of the detected facial feature(s) based on the reference feature. A patient interface size may be detected from standard patient interface sizes based on a comparison between the measured aspect of the facial feature(s) and a data record relating sizing information of the standard patient interface sizes and the measured aspect of the facial feature(s).