A pacification method based on emotion recognition, includes: acquiring at least one of a voice and an image of a user; determining whether the user has abnormal emotion, according to the at least one of the voice and the image of a user; and in response to the user having abnormal emotion, determining a pacification manner according to the emotion of the user, and performing emotional pacification on the user. An apparatus, a device and a storage medium are also provided.

Provided are systems and methods for providing personalized videos featuring multiple persons. An example method includes enabling a communication chat between a user of a computing device and at least one further user of at least one further computing device, receiving a user selection of a video from one or more personalized videos, receiving an image of a source face and a further image of a further source face, modifying the image of the source face to generate an image of a modified source face, modifying the further image of the further source face to generate an image of a modified further source face, replacing, in the video, a target face with the image of the modified source face and at least one further target face with the modified further source face to generate a personalized video, and sending the personalized video to the at least one further user.

Provided are a control system and method using an in-vehicle gesture input, and more particularly, a system for receiving an occupant's gesture and controlling the execution of vehicle functions. The control system using an in-vehicle gesture input includes an input unit configured to receive a user's gesture, a memory configured to store a control program using an in-vehicle gesture input therein, and a processor configured to execute the control program. The processor transmits a command for executing a function corresponding to a gesture according to a usage pattern.

An occupant monitoring device includes: an acquisition unit that acquires a captured image obtained by imaging a region in which there is a probability that a face of an occupant is present in a vehicle; a determination unit that determines whether the captured image acquired by the acquisition unit corresponds to a first image including the face a part of which is hidden by an accessory or a second image including the face a part of which is hidden by a non-accessory object other than the accessory; and a processing unit that detects face information regarding the face of the occupant based on the captured image in different modes according to a determination result in the determination unit, and monitors a state change of the face of the occupant based on a detection result.

A computer-implemented method includes obtaining a video of a subject, the video including a plurality of frames; generating, based on the plurality of frames, a plurality of optical flows; and encoding the plurality of optical flows using an autoencoder to obtain a movement-based biomarker value of the subject.

Image analysis is performed on a user at a transaction terminal. Based on behaviors, expressions, and activities of the user, fraud or potential fraud is flagged. When fraud is flagged, the transaction terminal stops processing an active transaction on behalf of the user and alerts are sent. When potential fraud is flagged, images/video associated with the active transaction are sent for review and the active transaction may be suspended or permitted to proceed at the transaction terminal. In an embodiment, a same user conducting multiple transactions with different accounts at a same transaction terminal or multiple different transaction terminals within a configured period of time is automatically identified as fraud based on a fraud rule.

Systems and methods are disclosed configured to train an autoencoder. A data training set is generated comprising images of different faces. A first autoencoder configuration is generated, comprising a first encoder, and a first decoder. The first autoencoder configuration is trained using dataset images, wherein weights associated with the first encoder and weights associated with the first decoder are modified. A second autoencoder configuration is generated comprising the first encoder and a second decoder. The second decoder is trained using images of a first target face. First encoder weights are substantially maintained, and weights associated with the second decoder are modified. An autoencoder comprising the trained first encoder and the trained second decoder generates an output using a source image of a first face having a facial expression, where the facial expression of the first face from the source image is applied to the first specific target face.

Embodiments described herein provide an approach of animating a character face of an artificial character based on facial poses performed by a live actor. Geometric characteristics of the facial surface corresponding to each facial pose performed the live actor may be learnt by a machine learning system, which in turn build a mesh of a facial rig of an array of controllable elements applicable on a character face of an artificial character.

A method and apparatus comprising generating a dynamic personalized webpage is disclosed. At least two webpages are loaded in a fashion that is hidden from the user. Content from the at least two webpages is extracted based on classification “of interest” by an artificial intelligence algorithm. A dynamic personalized webpage comprising extracted content is then generated and displayed to the user. In the preferred embodiment, the user's dynamic personalized webpage will be filled with advertisements tailored to the user and the user would receive at least some revenue from advertisements.

A system, method, and computer-readable media for obtaining the informed consent of a patient for a medical procedure. Specifically, a video describing a medical procedure may be provided to the patient through a client device having two display portions. As the video is playing in a first portion, the client device may capture the patient watching the video and display the captured image on the second portion. The entire display of the client device may be recorded, providing a record that the patient has watched the video describing the medical procedure and consents to the medical procedure.