Disclosed is a care device recommendation server providing a service for recommending a skin care device for a user, the care device recommendation server including: a data management unit configured to obtain face images of the user from a shin measurement device including a camera and a display; a skin condition determination unit configured to determine a first skin condition of the user corresponding to a first time point at which the face images are obtained, based on the obtained the face images; a care device recommendation unit configured to determine the skin care device for the user among a plurality of care devices included in a care device DB based on the determined first skin condition; a care device control value-providing unit configured to provide a first control value of the skin care device corresponding to the first skin condition to each of a user terminal of the user and the skin measurement device; a care device control unit configured to remotely control the care device such that the skin care device is driven by the control value; and a history provision unit configured to provide information about a previous skin condition of the user, which corresponds to each of the face images of the user obtained from the data management unit, to the user terminal.

A mobile device includes an application processor and an image sensor. The application processor includes an imaging subsystem configured to process high resolution image data through a first interface and a sensor hub configured to process sensor data through a second interface. The image sensor operates in one of first and second modes. The image sensor is configured to capture the high resolution image data in response to a request from the imaging subsystem and the imaging subsystem is configured to access the high resolution image data using the first interface for performing a first operation, during the first mode. The image sensor is configured to capture low resolution image data and the sensor hub is configured to access the low resolution image data using the second bus for performing a second operation, during the second mode.

An eye tracking system configured to: receive a plurality of right-eye-images of a right eye of a user; receive a plurality of left-eye-images of a left eye of a user, each left-eye-image corresponding to a right-eye-image in the plurality of right-eye-images; detect a pupil and determine an associated pupil-signal, for each of the plurality of right-eye-images and each of the plurality of left-eye-images; calculate a right-eye-pupil-variation of the pupil-signals for the plurality of right-eye-images and a left-eye-pupil-variation of the pupil-signals for the plurality of left-eye-images; and determine a right-eye-weighting and a left-eye-weighting based on the right-eye-pupil-variation and the left-eye-pupil-variation. For one or more right-eye-images and one or more corresponding left-eye-images, the eye tracking system can: determine at least one right-eye-gaze-signal based on the right-eye-image and at least one left-eye-gaze-signal based on the corresponding left-eye-image; and calculate a combined-gaze-signal from a weighted sum of the right-eye-gaze-signal and the left-eye-gaze-signal using the right-eye-weighting and the left-eye-weighting.

The present invention relates to a deep learning-based multiple skin lesion detection system, a multiple lesion detection method, and a computer-readable recording medium that has a program for implementing same recorded thereon. The system according to the present invention enables accurate classification and detection of various skin lesions having similar characteristics, on the basis of a context-dependent decision-making structure in which the local spatial correlation between various skin lesions in skin is considered.

There is a need to accurately and dynamically evaluate an individual's risk associated with the transmission or contraction of a disease. This need can be addressed, for example, by generation of a real-time or near real-time predicted disease score for an associated user. In one example, a method includes receiving a video stream data object depicting a visual representation of a target user; processing the video stream data object to generate a protective covering indication with respect to the target user; processing the video stream data object to generate a spatial proximity determination score with respect to the target user; processing the protective covering indication and spatial proximity determination score to generate a predicted disease score associated with the target user; and providing an augmented reality video stream data object configured to depict the visual representation of the target user and the predicted disease score.

An apparatus including an interface and a processor. The interface may be configured to receive pixel data. The processor may be configured to generate a plurality of video frames in response to the pixel data received from the interface, perform computer vision operations to detect objects in the video frames, extract features of the objects in response to characteristics of the objects determined using the computer vision operations, identify a person in the video frames based on the features, detect an event based on the person identified and generate a notification in response to detecting the event and a permission status. The permission status may suppress sending the notification when the permission status for the person identified corresponds to denying the notification and enable sending the notification when the permission status does not correspond to denying the notification.

An image processing system may include an imaging device for capturing an image and an image processing apparatus for processing the image. The imaging device may include an imaging unit for capturing the image, a first recording unit for recording information relating to the image, the information being associated with the image, and a first transmission control unit for controlling transmission of the image to the image processing apparatus. The image processing apparatus may include a reception control unit for controlling reception of the image transmitted from the imaging device, a feature extracting unit for extracting a feature of the received image, a second recording unit for recording the feature, extracted from the image, the feature being associated with the image, and a second transmission control unit for controlling transmission of the feature to the imaging device.

An eye tracking method comprising: capturing image data by an image sensor; determining a region of interest as a subarea or disconnected subareas of said sensor which is to be read out from said sensor to perform an eye tracking based on the read out image data; wherein said determining said region of interest comprises: a) initially reading out only a part of the area of said sensor; b) searching the image data of said initially read out part for one or more features representing the eye position and/or the head position of a subject to be tracked; c) if said search for one or more features has been successful, determining the region of interest based on the location of the successfully searched one or more features, and d) if said search for one or more features has not been successful, reading out a further part of said sensor to perform a search for one or more features representing the eye position and/or the head position based on said further part.

A method for generating a final image from an initial image including an object suitable to be worn by an individual. The presence of the object in the initial image is detected. A first layer is superposed on the initial image. The first layer includes a mask at least partially covering the object in the initial image. The appearance of at least one part of the mask is modified. The suppression of all or part of an object in an image or a video is enabled. Also, a process of augmented reality intended to be used by an individual wearing a vision device on the face, and a try-on device for a virtual object.

One embodiment of the present invention provides an image processing method, the method comprising: acquiring a plurality of viewpoint images; generating a contrast distribution from the plurality of viewpoint images; and generating an output image by performing image processing in accordance with the contrast distribution with respect to an image based on the plurality of viewpoint images.