Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.

Systems and methods enabling rendering an avatar attuned to a user. The systems and methods include receiving audio-visual data of user communications of a user. Using the audio-visual data, the systems and methods may determine vocal characteristics of the user, facial action units representative of facial features of the user, and speech of the user based on a speech recognition model and/or natural language understanding model. Based on the vocal characteristics, an acoustic emotion metric can be determined. Based on the speech recognition data, a speech emotion metric may be determined. Based on the facial action units, a facial emotion metric may be determined. An emotional complex signature may be determined to represent an emotional state of the user for rendering the avatar attuned to the emotional state based on a combination of the acoustic emotion metric, the speech emotion metric and the facial emotion metric.

In an embodiment, a virtual reality ride system includes a display to present virtual reality image content to a first rider, an audio sensor to capture audio data associated with a second rider, and an image sensor to capture image data associated with the second rider. The virtual reality ride system also includes at least one processor communicatively coupled to the display and configured to (i) receive the audio data, the image data, or both, (ii) generate a virtual avatar corresponding to the second rider, wherein the virtual avatar includes a set of facial features, (iii) update the set of facial features based on the audio data, the image data, or both, and (iv) instruct the display to present the virtual reality image content including the virtual avatar and the updated set of facial features.

Disclosed herein is a robot including an output interface including at least one of a display or a speaker, a camera, and a processor controlling the output interface to output content, acquiring an image including a user through the camera while the content is output, detecting an over-immersion state of the user based on the acquired image, and controlling an operation of releasing over-immersion when the over-immersion state is detected.

Systems and methods are disclosed for determining textual transcription from minute facial skin movements. In one implementation, a system may include at least one coherent light source, at least one sensor configured to receive light reflections from the at least one coherent light source; and a processor configured to control the at least one coherent light source to illuminate a region of a face of a user. The processor may receive from the at least one sensor, reflection signals indicative of coherent light reflected from the face in a time interval. The reflection signals may be analyzed to determine minute facial skin movements in the time interval. Then, based on the determined minute facial skin movements in the time interval, the processor may determine a sequence of words associated with the minute facial skin movements, and output a textual transcription corresponding with the determined sequence of words.

An example system includes a processor to receive an artificial intelligence (AI) model trained on a client device associated with a particular user. The processor is to filter a group message based on the AI model. The processor is to send the filtered group message to the client device.

Embodiments herein determine when to place a passive assistive call using personal artificial intelligence (AI) assistants. The present embodiments improve upon the base functionalities of the assistant devices by monitoring the usually discarded or filtered-out environmental sounds to identify when a person is in distress to automatically issue an assistive call in addition to or alternatively to monitoring user speech for active commands to place assistive calls. The assistant device may be in communication with various other sensors to enhance or supplement the audio assessment of the persons in the environment, and may be used in a variety of scenarios where prior call systems struggled to quickly and accurately identify distress in various monitored persons (e.g., patients) including falls, stroke onset, and choking.

Disclosed are systems and methods for template-based generation of personalized videos. An example method may commence with receiving video configuration data including a sequence of frame images, a sequence of face area parameters defining positions of a face area in the frame images, and a sequence of skin masks defining positions of a skin area of a part of the at least one body in the frame images. The method may continue with receiving an image of a source face. The method may further include determining color data associated with the source face. The method may include recoloring the skin area of the part of the at least one body in the frame image and inserting the image of the source face into the frame image at a position determined by face area parameters corresponding to the frame image to generate an output frame of an output video.

In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.

A computing device captures a live video of a user, determines a location of a facial region of the user by a facial region analyzer, and determines a finger vector type by a finger vector detector based on a direction in which at least one finger is pointing relative to the facial region of the user. Responsive to detecting a first finger vector type within the facial region involving a single finger, a makeup effects toolbar is displayed in the user interface. Responsive to detecting a second finger vector type involving the single finger, a selection tool for selecting a makeup effect in the makeup effects toolbar is displayed. The computing device obtains a makeup effect based on manipulation by the user of the selection tool. Responsive to detecting a target user action, virtual application of the selected makeup effect is performed on the facial region of the user.