Disclosed is an augmented reality system to generate and cause display of an augmented reality interface at a client device. Various embodiments may detect speech, identify a source of the speech, transcribe the speech to a text string, generate a speech bubble based on properties of the speech and that includes a presentation of the text string, and cause display of the speech bubble at a location in the augmented reality interface based on the source of the speech.

A mobile device can implement a neural network-based style transfer scheme to modify an image in a first style to a second style. The style transfer scheme can be configured to detect an object in the image, apply an effect to the image, and blend the image using color space adjustments and blending schemes to generate a realistic result image. The style transfer scheme can further be configured to efficiently execute on the constrained device by removing operational layers based on resources available on the mobile device.

An access control system can include a camera that detects an image regarding a subject, a database maintaining information, a facial recognizer that receives the image and identifies a facial feature of the subject based on the received image and the facial information maintained by the database, and a processor to alert security or another user when an authorized user accessing an area of a building is under duress, when an unauthorized user is accessing an area of a building by tailgating after an authorized user, when an authorized user has not provided two-factor authentication, or when an authorized user is in a particular area of the building.

A system for interactive product sampling and obtaining real-time consumer feedback to generate qualitative insights is described. The system may include an interactive imaging device, a sampling subsystem, a graphical user interface, a back-end system. The sampling subsystem dispenses product samples and obtains audio, video, or textual feedback from consumers. The system may perform sentimental and emotional analysis of video feedback to capture facial expressions and reactions of the consumer consuming the product samples. The system may use a trained model to generate qualitative insights from the feedback. Related methods, computer readable media, computer program product, apparatuses, and techniques are also described.

In a computer-implemented method of augmenting a dataset used in facial expression analysis, a first facial image and a second facial image are added to a training/testing dataset and mapped to two respective points in a continuous dimensional emotion space. The position of a third point in the continuous dimensional emotion space between the first two points is determined. Augmentation is achieved when a labelled facial image is derived from the third point based on its position relative to the first and second facial expression.

Systems and methods for educational analysis optimization. The system includes a camera, a processor and memory. The memory stores instructions to execute a method. The method begins with receiving a request from a user at a client device to begin a stimulus session. Then, video recording of the user for the stimulus session is initialized. Next, calibrations for emotions and gaze are set. Then, one or more stimuli are presented to the user. Cues and reactions are recorded and mapped to content that was displayed during the times of recorded reactions and cues. The recordings are post-processed for educational analysis and feedback is provided to the user. The feedback and analysis can be optimized using a predictive artificial intelligence model.

Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for synthesizing a realistic image with a new expression of a face in an input image by receiving an input image comprising a face having a first expression; obtaining a target expression for the face; and extracting a texture of the face and a shape of the face. The program and method for generating, based on the extracted texture of the face, a target texture corresponding to the obtained target expression using a first machine learning technique; generating, based on the extracted shape of the face, a target shape corresponding to the obtained target expression using a second machine learning technique; and combining the generated target texture and generated target shape into an output image comprising the face having a second expression corresponding to the obtained target expression.

An information processing apparatus in the present invention includes: an acquisition unit that acquires first history information indicating that a procedure related to boarding of a passenger in an airport was performed with biometric authentication and second history information indicating that the procedure was performed with reading of a medium; and an output unit that outputs usage status of the biometric authentication in the procedure based on the first history information and the second history information.

A video call mediation method of a system may include receiving, by a server, a mediation request, from a plurality of mobiles, mediating, by the server, a first mobile and a second mobile, of the plurality of mobiles, establishing, by the first mobile and the second mobile, a video call session, receiving, by the first mobile, a video, from the second mobile, through the video call session, detecting, by the first mobile, a certain input, reporting, by the first mobile, a video received in the server, in response to the certain input, ending, by the first mobile, the video call session with the second mobile, and establishing, by the first mobile, a video call session with a third mobile, and verifying, by the server, the reporting, and rejecting, by the server, additional mediation request of the second mobile.

A method and system for detecting facial expressions in digital images and applications therefore are disclosed. Analysis of a digital image determines whether or not a smile and/or blink is present on a person's face. Face recognition, and/or a pose or illumination condition determination, permits application of a specific, relatively small classifier cascade.