Disclosed are a facial beauty prediction method and device based on multi-task migration. The method includes: performing similarity measurement based on a graph structure on a plurality of tasks to obtain an optimal combination of the plurality of tasks; constructing a facial beauty prediction model including a feature sharing layer based on the optimal combination; migrating feature parameters of an existing large-scale facial image network to the feature sharing layer of the facial beauty prediction model; inputting facial images for training to pre-train the facial beauty prediction model; and inputting a facial image to be tested to the trained facial beauty prediction model to obtain facial recognition results.

A method is presented. The method includes determining a number of landmarks in an image comprising multiple pixels. The method also includes determining a number of channels for the image based on a function of the number of landmarks. The method further includes determining, for each one of the number of channels, a confidence of each pixel of the multiple pixels corresponding to a landmark. The method still further includes identifying the landmark in the image based on the confidence.

Embodiments herein provide a method and system for real time ROI detection in thermal face images based on a heuristic approach. The ROI of the thermal images, once detected, is then further used to detect temperature of a subject corresponding to the ROI. Unlike state of the art techniques, the heuristic approach is computationally less intensive and provides fast and accurate ROI detection even in case of occluded faces in a crowd with a single thermal image having a plurality of subject being scanned. The heuristics applied does not focus on face detection but directly on point of interest detection. Once the point of interest (ROI) is detected, it may be used for plurality of applications such as subject tracking and the like, not limited to subject or object temperature sensing since the method disclosed herein is easily implementable on low power devices.

A signal processing method includes obtaining, by a signal processing apparatus, a network delay time with respect to a device connected to the signal processing apparatus via a network, obtaining an input signal, determining an allowable upper limit of a delay time for an output signal corresponding to the obtained input signal based on the obtained network delay time and a total allowable delay time, selecting a signal processing having a longest delay time that is less than or equal to the allowable upper limit of the delay time, performing the selected signal processing on the obtained input signal, and transmitting the obtained input signal on which the selected signal processing has been performed, as the output signal, to the device connected to the signal processing apparatus via the network.

An example method includes outputting, by a computing device for display, one or more digital images that include a face of a user, receiving, by the computing device and based on a facial recognition process, an indication of a match between facial data associated with the face of the user and reference facial data associated with a face of an enrolled user of the computing device, and retrieving, by the computing device, digital makeup enhancement data that is associated with the reference facial data. The example method further includes applying, by the computing device, the digital makeup enhancement data to the facial data, of tire face of the user to generate one or more modified digital images that indicate at least one corresponding digital makeup enhancement to the face of the user, and outputting, by the computing device for display, the one or more modified digital images.

Data encryption and Human Pose Estimation based on imaging a body segment. A key for encrypting a data file is generated based on image data that represent a unique biometric feature of a body segment of a user or motion of the user. An image engine executes artificial intelligence to identify matching image data for decrypting the data file. The image engine is further trained to predict changes in image data due to aging, stress, and the like. An avatar associated with the user, which is generated based on a movement pattern of the user, is configurable for generating an encryption key and for use in an avatar-based language.

A drowsy driving detection method comprises: acquiring a side face image of a currently seated driver collected by a camera module; performing face recognition on the side face image to obtain side face feature parameters, and determining, according to the side face feature parameters, whether an ID file corresponding to the currently seated driver exists in a driver ID library; and if yes, periodically acquiring a side face image of the driver in the current period collected by the camera module, obtaining eye movement feature parameters of the driver in the current period according to the side face image of the current period, and determining whether the driver is driving while drowsy according to a comparison result between the eye movement feature parameters of the current period and the normal eye movement feature parameters of the driver.

An image providing apparatus (10) includes a registration unit (12) for registering a plurality of captured images of a predetermined user taken at a plurality of locations and captured times of the plurality of captured images, respectively, in a storage unit (11) in association with each other, a specification unit (13) for specifying two or more location captured images including a face area whose degree of match with a face area of the user included in a specific image captured at a specific location is greater than or equal to a predetermined value from among the plurality of captured images, and an output unit (15) for outputting the two or more specified location captured images in order of the captured times.

Provided are methodology and system countering fraudulent document and/or image use when authentication of a transaction based on a given document or image use is required. Additionally provided is a manner of machine learning adapting the methodology for implementation thereof.

An artificial intelligence device can include a display configured to display an avatar image, a processor configured to detect a user's face region from an image received from a camera, extract a preset number of feature points from the detected face region, and transmit information about the extracted feature points to a graphic engine, and the graphic engine configured to output, to the display, an avatar face image corresponding to the face region based on the information about the feature points.