Provided are a face feature point detection method, applied to an image processing device, where the image processing device stores a feature area detection model and a feature point detection model. The method includes: preprocessing a face image to be detected to obtain a preprocessed target face image; performing feature point extraction on the target face image according to the feature area detection model and the feature point detection model to obtain a target feature point coordinate located within a face feature area in the target face image; and performing coordinate transformation on the target feature point coordinate to obtain a face feature point coordinate corresponding to the face image to be detected. Further provided are a face feature point detection device, an equipment and a storage medium.

Tracking units for facial features with advanced training for natural rendering of human faces in real-time are provided. An example device receives a video stream, and upon detecting a visual face, selects a 3D model from a comprehensive set of head orientation classes. The device determines modifications to the selected 3D model to describe the face, then projects a 2D model of tracking points of facial features based on the 3D model, and controls, actuates, or animates hardware based on the facial features tracking points. The device can switch among an example comprehensive set of 35 different head orientation classes for each video frame, based on suggestions computed from a previous video frame or from yaw and pitch angles of the visual head orientation. Each class of the comprehensive set is trained separately based on a respective collection of automatically marked images for that head orientation class.

A hearing aid system for individual identification of a hearing aid system may include a wearable camera, a microphone, and at least one processor. The processor may be programmed to receive a plurality of images captured by the wearable camera; receive audio signals representative of sounds captured by the microphone; and identify a first audio signal, from among the received audio signals, representative of a voice of a first individual. The processor may transcribe and store, in a memory, text corresponding to speech associated with the voice of the first individual and determine whether the first individual is a recognized individual. If the first individual is a recognized individual, the processor may associate an identifier of the first recognized individual with the stored text corresponding to the speech associated with the voice of the first individual.

The present disclosure provides a method for extracting a face detection image, wherein the method includes: obtaining a plurality of image frames by an image detector, performing a face detection process on each image frame to extract a face area, performing a clarity analysis on the face area of each image frame to obtain a clarity degree of a face, conducting a posture analysis on the face area of each image frame to obtain a face posture angle, generating a comprehensive evaluation index for each image frame in accordance with the clarity degree of the face and the face posture angle of each image frame, and selecting a key frame from the image frames based on the comprehensive evaluation index. Such that the resource occupancy rate during image data processing may be reduced, and the quality of the face detection process may be improved.

Systems and methods for using image analysis techniques to assess unsafe driving conditions by a vehicle operator are discloses. According to aspects, a computing device may access and analyze image data depicting the vehicle operator. In analyzing the image, the computing device may measure certain visible metrics as depicted in the image data and compare the metrics to corresponding threshold values, and may accordingly determine whether the vehicle operator is exhibiting an unsafe driving condition. The computing device may generate and present alerts that indicate any determined unsafe driving condition.

For scanning optical patterns, such as two-dimensional QR codes, with a mobile device at increased distances, a first image is acquired. A region of interest likely containing the optical pattern in the first image is identified. The mobile device then zooms in on the region of interest and a second image is acquired. The optical pattern is then decoded using the second image.

Methods and systems are described for maintaining hygienic conditions in automatic teller machines by detecting whether or not a user is not in compliance with a hygienic standard. If a user is not in compliance, then the automatic teller machine may execute a hygienic action to cleanse the automatic teller machine. For example, the hygienic action may comprise automatically cleansing the automatic teller machine, disabling the automatic teller machine from service, transmitting a sanitation service request to an automatic teller machine provide, and/or initiating an alternative control scheme (e.g., voice controls, gesture-based controls, etc.) for the automatic teller machine.

A method for operating a messaging system for sending modifiable videos including a self-image of a user is provided. The method includes providing a face outline to assist with taking the self-image. Instructions relating to a light level, a facial expression, a face position, and a face size may be provided to the user. A smile measurement is displayed to enable the user to adjust the current smile level to a target smile level. A stock video may be created using an actor wearing a mask and facing a video camera. The mask is a marker for insertion of the self-image. The stock video is uploaded to a database of stock videos and, after selection by a user, is combined with a self-image to form a personalized video.

A face image processing method and apparatus, a readable medium, and an electronic device, relates to the field of image processing technologies. The method includes: obtaining (101) sight line information in a face image to be processed in accordance with a preset recognition algorithm, where the sight line information includes: a first coordinate and an edge coordinate for an eye, and the edge coordinate is used to indicate an intersection of a sight line of an eye and an edge of the face image; determining (102) a target area in the face image according to the sight line information, where the target area includes a sight line segment with the first coordinate and the edge coordinate as endpoints; and rendering (103) a preset effect material to target area to obtain a target image.

Implementations described herein relate to methods, systems, and computer-readable media for remote production collaboration tools. The remote production collaboration tools can include one or more client devices, a server providing a single connection point, and an animation server configured to produce an animated production. The one or more client devices may provide motion capture data, audio data, control data, and/or associated timestamps. The animation server is configured to process the motion capture data, audio data, control data, and/or the associated timestamps and create the animated production. The animated production may be transmitted as a video stream.