14 results about "Facial analysis" patented technology

The invention relates to a method for identifying a person in the vicinity of a motor vehicle using sensors arranged on the vehicle, the method comprising the following steps when the person approaches the motor vehicle: a) detecting their gait by means of the sensors, analysing at least one gait-related parameter, comparing it with previously recorded and established gait models and calculating a gait recognition score; b) detecting the face of the person by means of the sensors, analysing at least one parameter of the face, comparing it with previously recorded and established face models and calculating a face recognition score; c) normalising the scores according to reference scores; d) fusing the normalised gait recognition and face recognition scores in order to identify whether or not the person is associated with the motor vehicle.

The invention provides an image generation method and apparatus, a computing device, a storage medium and a program product. The image generation method comprises the steps of obtaining a reference image and an initial image; performing object face analysis on the reference image to obtain a face attribute feature of a first object in the reference image, and performing feature extraction on the initial image based on a second object in the initial image to obtain an image feature; and based on the facial attribute features and the image features, generating a target image fusing the facial attributes of the first object. The technical effects that it can be ensured that the generated target image has the core facial features of the reference image uploaded by the user without a complex style migration process, the image is adaptive to the style of the initial image during generation, and meanwhile the facial attributes of the facial image uploaded by the user can be restored are achieved.

The invention provides an emotional feature recognition system and method for classroom teaching. The method comprises the following steps: acquiring facial image data and behavior time sequence data of a student in a classroom teaching process through a camera after the student clearly knows and agrees to authorize; determining dynamic expression features of the student through a preset facial analysis model according to the facial image data; on the basis of a head posture change sequence and an eye fixation focus track extracted from behavior time sequence data, constructing concentration indexes and confusion indexes of students in different teaching links through multi-feature fusion; and when it is detected that a preset condition is met, generating an emotional feature tag of the student in classroom teaching based on the dynamic expression feature, the concentration index and the confusion index, and pushing the emotional feature tag to a teacher terminal for visual display. By adopting the scheme of the invention, multi-modal feature fusion analysis of the classroom state of the student can be realized, so that the accuracy of classroom teaching regulation and control is improved.

This invention discloses a method and apparatus for visualizing four-region facial segmentation based on a 3D model, relating to the field of image processing technology. The method includes: calculating the unit normal of each vertex; extracting specular transition rings and generating a ring buffer set; performing weighted statistical analysis on mesh vertices using suppression weights to establish the left-right and top-bottom axes of the 3D face mesh; projecting the vertex set onto the left-right and top-bottom axes, and determining the left-right segmentation boundary and top-bottom segmentation threshold based on the ring buffer set to generate a four-region mask; performing ring attenuation backfilling processing on the scalar values ​​of the vertices to be visualized based on geodesic distance to obtain the visualization scalar values, and calculating the statistical indicators of each region based on the suppression weights and the four-region mask. This invention can significantly improve the stability and accuracy of 3D facial analysis.

The cabin atmosphere mode control system comprises an emotion recognition module, a voice recognition module and a control module, wherein the emotion recognition module comprises a face recognition unit and a voice recognition unit; the emotion analysis module comprises a face analysis unit and a voice analysis unit; the face analysis unit is used for analyzing the face image acquired by the face recognition unit and inputting a basic emotion label and a corresponding score; the voice analysis unit analyzes the voice signals collected by the voice recognition unit, performs weighted fusion on acoustic features and semantic features, and outputs various basic emotion tags and corresponding scores; when the face analysis unit and the voice analysis unit work at the same time, the emotion analysis module adopts a conservative discrimination mechanism to add scores of the face emotion label and the voice emotion label and then outputs a comprehensive emotion label according to a preset frequency; and the cabin adjusting module can adjust corresponding cabin components according to the comprehensive emotion label.

Systems and methods for enrolling and authenticating a user in an authentication system via a user's camera of camera equipped mobile device include capturing and storing enrollment biometric information from at least one first image of the user taken via the camera of the mobile device, capturing authentication biometric information from at least one second image of the user, capturing, during imaging of the at least one second image, path parameters via at least one movement detecting sensor indicating an authentication movement of the mobile device, comparing the authentication biometric information to the stored enrollment biometric information, and comparing the authentication movement of the mobile device to an expected movement of the mobile device to determine whether the authentication movement sufficiently corresponds to the expected movement.

Methods, apparatus, systems, and articles of manufacture for applying selective adjustment of displays are disclosed herein. An example apparatus to control an operating characteristic such as a brightness of a display of an electronic device includes a face analyzer to identify a presence of a face of a user relative to the device based on image data generated by an image sensor of the electronic device, and a correlation analyzer to determine a correlation of the detected presence and a first device interaction event. In response to the correlation, the correlation analyzer is to apply a display brightness adjustment rule to selectively adjust the brightness of the display from a first setting to a second setting after a first time interval.

The invention relates to the field of face capture, in particular to a VR virtual character interaction system and method based on user-defined expression and mouth shape synchronization, and the system comprises a data collection unit which is used for collecting face data of a target user; the face analysis unit is used for determining a paragraph division mode according to the face analysis state; the paragraph division unit is used for executing a paragraph division The point location processing unit is used for judging whether the sub-region is a target sub-region or not according to the motion trend median value, determining a range setting mode according to the influence coefficient difference degree of the first key point and determining a second key point setting strategy according to the motion state of the first key point; according to the invention, the virtual character interaction effect is improved.

The present disclosure relates to a system (102) and a method for facial analysis based on facial areas of interest (ROIs) in a vehicle. The system (102) comprises an image acquisition unit (106) that captures images of the user. The system (102) comprises a detection module (108) that detects one or more landmarks corresponding to one or more facial features in the images. The system (102) comprises a control unit (104) for analyzing one or more detected landmarks to determine one or more unobstructed ROI landmarks and one or more concealed ROI landmarks in one or more images. The control unit (104) constructs a predefined area based on one or more unobstructed ROI landmarks in one or more images.Control unit (104) calculates one or more facial features based on one or more unobstructed ROI reference points and a predefined area. Control unit (104) performs a facial feature analysis based on the classification of unobstructed ROI reference points into face-selected reference points and non-face-selected reference points in images (302).

An object of a system according to an embodiment is to propose optimal makeup to a user and explain a procedure thereof.SOLUTION: A system according to an embodiment includes a face analysis unit, a makeup suggestion unit, a makeup simulation unit, and a makeup procedure explanation unit. The face analysis unit analyzes features of the face of the user. The makeup suggestion unit suggests optimal makeup based on the feature analyzed by the face analysis unit. The makeup simulator applies the makeup proposed by the makeup proposal unit to the face of the user. The makeup procedure explanation unit explains a makeup procedure applied by the makeup simulation unit.SELECTED DRAWING: Figure 1

The application discloses a kind of intelligent simulation simulation method and system of facial microplasty operation, it is related to image processing technical field, the intelligent simulation simulation method is by obtaining high-precision facial data, and accurately calibrates facial defect site, and after facial three-dimensional image data is handled by normalization, key facial features are extracted by deep learning algorithm, provide basis for microplasty scheme.Different types of data are integrated by intelligent fusion technology, form comprehensive facial analysis atlas, support virtual simulation and surgical effect evaluation.Then automatically generate personalized surgical plan, predict postoperative effect, provide accurate operation strategy, such as material selection, injection depth and complication risk, significantly reduce surgical risk.System combines patient feedback, real-time adjustment scheme, and postoperative effect evaluation is carried out, ensure that effect meets expectation.

1. Name of the product in this design: Graphical User Interface for Facial Analysis Display of Electronic Device. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photo that best illustrates the design points: Interface change state diagram 1. 5. Purpose of the Graphical User Interface: This graphical user interface is used for facial analysis. After the user uploads a photo by clicking the "Upload Photo and Receive Report" button in the main view, the interface transitions to state 1. The system automatically scans the photo to analyze the user's facial features, resulting in state 2. Analysis of the corresponding facial features appears below the scan progress. After the analysis is complete, the interface transitions to state 3. Clicking the "Add" button in state 3 leads to state 4. State 4 is the facial analysis report page. Swiping up on state 4 leads to state 5 through 8. Gray blocks in the interface represent replaceable images or videos, and "XXXX" represents character or text content.

A system and method for more accurately and robustly determining a characteristic of a subject from an image of the subject.SOLUTION: Determining, using the parallel processing circuitry, landmark points of the subject and corresponding confidence values, wherein the confidence values correspond to an amount of occlusion of portions of the subject image data corresponding to the respective landmark points, and using the landmark points and the confidence values to monitor a state of the subject, wherein the one or more machine learning models are a first set of one or more machine learning models; The method where the using further includes transmitting the landmark points and the confidence values for use with a second set of one or more machine learning models configured to generate as output at least one of the gaze direction of the subject, the head pose of the subject, or the drowsiness state of the subject.SELECTED DRAWING: Figure 2