A system for authenticating a user attempting to access a computing device or a software application executing thereon. A data storage device stores one or more digital images or frames of video of face(s) of authorized user(s) of the device. The system subsequently receives from a first video camera one or more digital images or frames of video of a face of the user attempting to access the device and compares the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device. To ensure the received video of the face of the user attempting to access the device is a real-time video of that user, and not a forgery, the system further receives a first photoplethysmogram (PPG) obtained from a first body part (e.g., a face) of the user attempting to access the device, receives a second PPG obtained from a second body part (e.g., a fingertip) of the user attempting to access the device, and compares the first PPG with the second PPG. The system authenticates the user attempting to access the device based on a successful comparison of (e.g., correlation between, consistency of) the first PPG and the second PPG and based on a successful comparison of the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device.

A method selectively activates a resource to accommodate an advanced emotion. A supervisor computer receives a first piece of content, and then applies an emotion classifier to the first piece of content in order to create a first concept/emotion/sentiment/time tuple. The supervisor computer creates a second concept/emotion/sentiment/time tuple for a second piece of content, and compares the first and second tuples. If the concept in the first piece of content matches the concept in the second piece of content but that at least one of the emotion, sentiment, and time of the first piece of content does not match the emotion, sentiment, and time of the second piece of content, the supervisor computer determines that the emotion of the second piece of content is an advanced emotion that is not expressed by the first or second pieces of content, and activates a resource that accommodates the advanced emotion.

A control apparatus is provided, including: an other-vehicle emotion acquiring unit configured to acquire an other-vehicle emotion indicating an emotion of an occupant of a second vehicle different from a first vehicle; a determination unit configured to determine whether to perform notification to an occupant of the first vehicle based on the other-vehicle emotion; and a notification control unit configured to perform control to notify the occupant of the first vehicle of notification information based on the other-vehicle emotion when the determination unit determines to perform the notification.

A control apparatus is provided, including: an other-vehicle emotion acquiring unit configured to acquire an other-vehicle emotion indicating an emotion of an occupant of a second vehicle different from a first vehicle; a determination unit configured to determine whether to perform notification to an occupant of the first vehicle based on the other-vehicle emotion; and a notification control unit configured to perform control to notify the occupant of the first vehicle of notification information based on the other-vehicle emotion when the determination unit determines to perform the notification.

A computer-implemented method for implementing face recognition includes receiving training data including a plurality of augmented images each corresponding to a respective one of a plurality of input images augmented by one of a plurality of variations, splitting a feature embedding generated from the training data into a plurality of sub-embeddings each associated with one of the plurality of variations, associating each of the plurality of sub-embeddings with respective ones of a plurality of confidence values, and applying a plurality of losses including a confidence-aware identification loss and a variation-decorrelation loss to the plurality of sub-embeddings and the plurality of confidence values to improve face recognition performance by learning the plurality of sub-embeddings.

Sign language information processing method and apparatus, an electronic device and a readable storage medium provided by the present disclosure, achieve real-time collection of language data in a current communication of a user by obtaining voice information and video information collected by a user terminal in real time; and then match a speaking person with his or her speaking content by determining, in the video information, a speaking object corresponding to the voice information; and finally, make it possible for the user to clarify the corresponding speaking object when the user sees AR sign language animation in a sign language video by superimposing and displaying an augmented reality AR sign language animation corresponding to the voice information on a gesture area corresponding to the speaking object to obtain a sign language video. Therefore, it is possible to provide a higher user experience.

A first electronic device according to various embodiments may include: a display; a communication module comprising communication circuitry; a camera module including at least one camera; and a processor. The processor may be configured to: identify a request for measuring a skin condition of a user in a state in which the first electronic device is cradled on a second electronic device; acquire, based on information of the camera module and information regarding at least one light-emitting element included in the second electronic device, control information for controlling output of the at least one light-emitting element; control output of light from the at least one light-emitting element of the second electronic device based on the control information; acquire at least one image including at least a part of a body of the user through the camera module while light is output through the at least one light-emitting element controlled based on the control information; and provide information regarding the skin condition of the user using the at least one image.

There is provided an image processing system and method for identifying a user. The system comprises a processor configured to identify a first user in an image, determine a plurality of characteristic vectors associated with the first user, compare the characteristic vectors associated with the first user with a plurality of predetermined characteristic vectors associated with a plurality of users including the first user, and identify the first user based on the comparison.

An information processing method and an electronic device are provided. The method is performed by a first wearable device, where the first wearable device includes a first image collector, and the method includes: obtaining a second face image by the first image collector and receiving a first face image from the second wearable device in a case that the first wearable device and a second wearable device are in a preset positional relationship; and processing first target information from the second wearable device in a case that the first face image matches the second face image.

A face liveness detection method is provided, and includes: receiving an image transmitted by a terminal, the image including a face of an object; performing data augmentation on the image, to obtain an extended image corresponding to the image, a number of extended images corresponding to the image being more than one; performing liveness detection on the extended images corresponding to the image, to obtain intermediate detection results of the extended images, a liveness detection model used in liveness detection being obtained by performing model training on an initial neural network model according to a sample image and extended sample images corresponding to the sample image; and obtaining a liveness detection result of the object in the image after fusing the intermediate detection results of the extended images.