In some examples, the disclosure describes a device, comprising: a processor resource, and a non-transitory memory resource storing machine-readable instructions stored thereon that, when executed, cause the processor resource to: determine an emotion based on a facial expression of a user captured within an image, apply a plurality of alterations to the image to exaggerate the facial expression of the user when the emotion has continued for a threshold quantity of time, and remove the plurality of alterations to the image when the emotion of the user has changed.

In some implementations, a device may determine an interaction profile for a provider that is to engage with a user in a communication session. The interaction profile may be based on interaction data relating to interpersonal interactions involving the provider during one or more previous communication sessions. The interaction profile may indicate a bias of the provider in connection with one or more categories of users. The device may generate, based on the interaction profile, a visual representation that depicts at least a face of a person for presentation to the provider during the communication session. One or more characteristics associated with the one or more categories of users may be absent from the face of the person. The device may cause presentation of the visual representation to the provider during the communication session.

A non-transitory computer-readable recording medium stores a program that causes a computer to execute a process, the process includes inputting each of first images that includes a face of a subject to a first machine learning model to obtain a recognition result that includes information indicating first occurrence probability of each of facial expressions in each first image, generating training data that includes the recognition result and second images that are respectively generated based on the first images and in which at least a part of the face of the subject is concealed, and performing training of a second machine learning model, based on the training data, by using a loss function that represents an error that relates to a second occurrence probability of each facial expression in each second image and relates to magnitude relationship in the second occurrence probability among the second images.

A method, computer system, and a computer program product for image evaluation is provided. The present invention may include extracting one or more individual objects from an image. The present invention may include determining a general sentiment for each of the one or more individual objects. The present invention may include determining a personal sentiment score each of the one or more individual objects. The present invention may include generating an overall sentiment score for the image based on at least the general sentiment score for each of the one or more individual objects and the personal sentiment score for each of the one or more individual objects. The present invention may include determining the overall sentiment score for the image exceeds a personal threshold of a user. The present invention may include providing one or more improvement mechanisms to the user.

A method of adaptively updating an enrollment database is disclosed. The method may include extracting a first feature vector from an input image, the input image including a face of a user, determining whether to enroll the input image in the enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, and enrolling the input image in the enrollment database based on a result of the determining.

An electronic apparatus is provided. The electronic apparatus includes a user interface, a camera, a memory configured to store a first artificial intelligence model trained to obtain information on an emotion based on an input image, and a processor, connected to the user interface, the camera, and the memory, configured to control the electronic apparatus. The processor is configured to, based on text being input through the user interface, identify whether the text includes first information on a user's emotion, based on the text including the first information, obtain second information for the emotion by inputting the image obtained through the camera to the first artificial intelligence model, and identify a type of the user's emotion based on the first information obtained from the text and the second information obtained from the image.

A method for predicting a condition of living-being in an environment, the method including capturing image-data associated with the at-least one person and based thereupon determining a current-condition of the person; receiving content from a plurality of content-sources with respect to said at least one person being imaged, said content defined by at least one of text and statistics; defining one or more weighted parameters based on allocating a plurality of weights to at least one of the captured image data and the received content based on the current-condition; and predicting, by a predictive-analysis module, a condition of the at-least one person based on analysis of the one or more weighted parameters.

In one aspect, a first device may include at least one processor and storage accessible to the at least one processor. The storage may include instructions executable by the at least one processor to, during video conferencing and based on at least one identified condition (such as an issue with a network being used for the video conferencing), select a first image from plural images received from a camera. The plural images may be associated with the video conferencing. The instructions may also be executable to provide the first image to a second device different from the first device but decline to provide at least a second image from the plural images.

A method of processing the psychophysical state of a driver to improve the driving experience of road vehicle driven by a driver and comprising the steps of: cyclically detecting one or more objective vital parameters of the driver by means of one or more first sensors installed within a vehicular system; processing the value of a vital state index according to said one or more objective vital parameters detected; cyclically detecting one or more subjective parameters of the driver by means of one or more second sensors installed within the vehicular system; processing, starting from the objective vital parameters and according to the subjective parameters, the psychophysical state of the driver.

The present disclosure provides a display method and a display device for an interactive interface and a computer-readable storage medium. The display method for the interactive interface includes: determining, from at least one object, a target object to interact through the interactive interface; acquiring an attribute information of the target object and an emotion information of the target object; and controlling a display of a first object region of the interactive interface according to the attribute information of the target object and the emotion information of the target object.