81 results about "Face matching" patented technology

To enable improvement in the accuracy of authentication regardless of surrounding environments.SOLUTION: A face authentication gate system includes a gate device, a control device, and a face authentication server, and determines whether a user is permitted to pass a gate device or not on the basis of a result of face collation processing between registered face information registered in advance and captured face information based on a captured image. The face authentication server transmits a face collation score, which is a score for face collation between registered face information and captured face information based on an image of a user who is trying to pass the gate device, to the control device. The control device controls a parameter related to imaging on the basis of illuminance of a captured image when the face collation score is at an illuminance evaluation threshold or more and is less than an evaluation upper limit value.SELECTED DRAWING: Figure 1

A display apparatus includes: a display panel including a plurality of pixels; a data driver which applies data voltages to the pixels; a gate driver which applies gate signals to the pixels; and a driving controller which controls the data driver and the gate driver. The driving controller divides the display panel into a plurality of panel blocks, calculates a skin color inclusion ratio of each of the panel blocks based on input image data, determines at least one face region candidate block among the panel blocks based on the skin color inclusion ratio, determines a face region block of the at least one face region candidate block based on the at least one face region candidate block and face matching data, and performs image quality processing on the face region block.

The Biometric Recognition and Transaction Engine Apparatuses, Processes and Systems (“BRTE”) transforms enrollment input, authentication input datastructure / inputs via BRTE components into enrollment output, authentication output outputs. A device identifying datastructure associated with a user's device is obtained. A device search is executed on a device graph database to determine a device record corresponding to the device and a device token is retrieved. A user identifying media datastructure structured as a media stream is obtained. A face print datastructure and a voice print datastructure are generated. A user seed identifying datastructure is obtained and analyzed to determine a user token. A set of face token records and a set of voice token records linked with the user token are determined. A face match score and a voice match score are determined and analyzed to authenticate the user. A login token indicating successful authentication is generated and provided for the device.

The application relates to the field of face recognition, in particular to a 5G recorder face recognition pre-filtering method and system, which comprises an image capturing module, a face feature extraction module, a face characteristic dimension reduction and normalization module, a face library module, a face filtering tree module, a face pre-filtering module, a face characteristic block module and a face hierarchical comparison module. The face feature filtering tree method is used to realize face matching pre-filtering of 5G recorders and other equipment. The face library is blocked according to normalized face characteristics, a hierarchical method is realized according to face feature matching strings for block matching, a matching face is found as much as possible, and the calculation amount of a server is reduced.

This invention discloses a method, apparatus, device, and storage medium for generating a virtual face. The method includes acquiring a real face image; generating multiple partial sub-images corresponding to the real face image, each including predefined facial elements; determining the type of facial elements in each partial sub-image based on an image feature set corresponding to each partial sub-image and a geometric feature set of facial elements; determining target standard face-shaping parameters corresponding to each facial element in the real face image based on the type of facial elements in each partial sub-image and preset standard face-shaping parameters corresponding to each type of facial element; and forming a virtual face matching the real face image based on the target standard face-shaping parameters corresponding to each facial element in the real face image. The technical solution of this invention achieves accurate identification of facial features, accurate classification of facial features, and precise generation of virtual faces.

A notification system notifies users when there is a match between images. The notification system includes a network interface receiving images from a plurality of user devices including a first user device and a second user device, a memory storing database and instructions, and a processor. The processor executes the instructions to function as an image processing unit processing the received images, a face recognition unit recognizing one or more faces in each received image, a face matching unit checking whether a face in a first image from the first user device matches a face in a second image from the second user device, a metadata processing unit processing metadata in each received image, and a notification unit notifying the first user device and the second user device in a case where the face in the first image matches the face in the second image.

The present invention discloses a face recognition method and system for a smart lock with multiple entries. The method includes: extracting facial information and body information of multiple entries within a capture time period; if facial images and body images are simultaneously extracted from the same person image, direct pairing is successful; if a unique pairing relationship is determined by the elimination method, pairing is successful; by searching a list of trajectories for multiple entries, calculating the similarity of the body information, and if the similarity is greater than a preset threshold, pairing is successful; for the body information that is not successfully retrieved, constructing its spatiotemporal trajectory sequence, and performing compatibility calculation with the face clustering spatiotemporal trajectory sequence in the list of trajectories for multiple entries to determine the confidence level; fusing the various pairing results, and for each face information corresponding to the body image information, taking the face matching result with the highest confidence level as the fusion result. Utilizing the embodiments of the present invention, it is possible to construct a confident identification of the results of multiple entries, thereby realizing the recognition of multiple entries.

This improves authentication accuracy regardless of the surrounding environment. [Solution] The facial recognition gate system has a gate device, a control device, and a facial recognition server, and determines whether or not a user can pass through the gate device based on the results of a facial matching process between pre-registered facial information and photographed facial information based on a captured image. The facial recognition server transmits the results of the facial matching process between the registered facial information and photographed facial information based on a captured image of a user attempting to pass through the gate device to the control device, and the control device controls parameters related to photography based on the illuminance of the captured image when the results of the facial matching process satisfy a first condition.

To provide a passage permission determination system, passage permission determination method and program capable of shortening a time required for authenticating an object person of authentication.SOLUTION: An information processing device executes face collation processing, when there is a user whose face collation processing result satisfies a second criterion, transmits an authority determination request to a determination device, when the authority determination result is received and the face collation processing result satisfies a first criterion, transmits information representing face collation success and the authority determination result, and when the authority determination result is received and the face collation processing result does not satisfy the first criterion, transmits information representing face collation failure and the authority determination result. When the received authority determination result represents that the user has authority and the information representing the face collation success is received, a gate device determines to allow the user to pass through the gate device, and when the authority determination result represents that the user has authority and the information representing the face collation failure is received, reserves the determination.SELECTED DRAWING: Figure 5

The application provides a pose matching method of a planar object, comprising: acquiring a point cloud of the planar object; extracting an edge point cloud based on the point cloud of the planar object; calculating edge vectors of the edge point cloud, wherein the edge vectors comprise a principal normal vector, a tangent vector or an edge normal vector; constructing a point pair feature vector set of any two points in the edge point cloud according to the principal normal vector, the tangent vector or the edge normal vector; and matching the point pair feature vector in the edge point cloud with a reference point pair feature vector set to obtain the pose of the planar object. The technical scheme of the application matches based on the edge normal, solves the problem that the matching of the planar object cannot be realized based on the face matching or the principal normal matching in the prior art, has high reliability and strong stability, and greatly improves the recognition accuracy and recognition efficiency of the planar object.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of medical health, financial science and technology and the like, and discloses a screen sliding behavior detection method, which comprises the following steps: acquiring video data and a target face image, detecting face feature information from the video data, and determining the position of a target face in a video by combining the target face image, and extracting video frames from the video data according to a preset time interval, inputting the video frames into the screen sliding classification model to obtain classification tags, removing unknown position tags and target face position tags from the classification tags to obtain residual screen sliding action tags, and when the number of the residual screen sliding action tags is not null, determining that a screen sliding behavior exists. According to the method, the video classification technology and the face detection matching technology are combined, the specific occurrence position of the screen sliding action is accurately judged in the screen sliding action detection process, the operation main body in the multi-role scene is effectively distinguished, the false alarm problem caused by matching of the hand and the face is avoided, and the false alarm rate and the missing report rate can be reduced.

The application discloses a head reconstruction method based on generation and inverse rendering collaborative optimization, comprising the following steps: step 1, generating a corresponding binary mask; step 2, fitting a three-dimensional geometric grid of a face matched with an input person based on detected two-dimensional face key points to obtain a unified head coordinate system; step 3, projecting pixels of an input image to a UV space of the three-dimensional geometric grid of the face to form a defective texture with original illumination and self-occlusion; performing illumination regularization and an inverse rendering network to output a multi-channel PBR material map; step 4, generating a group of videos rotating around the head and camera internal and external parameters thereof, and cutting the videos into a multi-view hair image sequence and corresponding virtual camera parameters; step 5, performing multi-view hair reconstruction to obtain a hair geometry representation or equivalent geometry representation representing a three-dimensional structure of hair; and step 6, performing spatial alignment and combination to output a head PBR three-dimensional asset.

The invention discloses a special effect differentiation processing system based on face recognition processing, and relates to the technical field of image processing, a face recognition module processes an image in real time to obtain face data, and a face weight distribution module calculates a weight based on a contour position, an area and features of five sense organs; the special effect distribution module matches special effects of corresponding computing power for different faces according to weights, the similar expression stabilization module dynamically evaluates the stability of special effect generation through statistical analysis, intelligent distribution and optimization of special effect resources are achieved, the key face special effect is improved, and computing power consumption is reduced. Priorities are distributed for different faces through a face weight distribution module (position, area and feature weight of five sense organs), high computing power special effects are generated only for high-weight faces by combining computing power grading (special effect cell division) of a special effect distribution module, and low-weight faces are matched with lightweight or do not generate special effects.

A vision-based target tracking method, a system, an equipment, and a storage medium. The method includes: acquiring face positions and body positions in a current image frame; acquiring a current position of a time-series tracking target by a time-series tracking algorithm; determining, when a face matching the face of a to-be-tracked target does not exist outside a region corresponding to the current position of the time-series tracking target, whether the time-series tracking target is in an intersecting state; determining whether a body matching the body of the to-be-tracked target in other persons intersecting the times-series tracking target when in the intersecting state, or using the current position of the time-series tracking target as a current target position if not in the intersecting state; and taking the current target position as the position of the to-be-tracked target in the previous frame, and returning to the above steps.

The invention relates to the technical field of project acceptance, and discloses an electronic signboard acceptance method and system based on face and fingerprint recognition, and the method comprises the steps: obtaining the position data of each electronic signboard in a project, and determining the acceptance personnel data of the corresponding electronic signboard according to the position data of each electronic signboard; obtaining acceptance personnel fingerprint information collected by the current electronic signboard, and determining fingerprint matching parameters according to the acceptance personnel fingerprint information; obtaining acceptance personnel face information collected by the current electronic signboard, and determining face matching parameters according to the acceptance personnel face information; and evaluating the acceptance quality of the current project according to the fingerprint matching parameters and the face matching parameters of the acceptance personnel. According to the invention, the fingerprint and face information of the project acceptance personnel can be collected through the electronic signboard, the acceptance accuracy of project acceptance is effectively improved, and the probability of safety accidents is reduced.

The invention discloses a face recognition system and method for construction site personnel training and on-duty dynamic verification, and the system comprises a video stream obtaining module which is used for obtaining an image frame sequence of construction site training; the human body detection module is used for obtaining each human body detection frame in each image frame and corresponding coordinate data; the tracking matching module is used for obtaining a tracking identifier of each human body detection frame; the first judgment module is used for judging whether the tracking identifier of each human body detection frame is a newly added tracking identifier or not; the face detection module is used for obtaining a face image quality score; the second judgment module is used for judging whether the face image quality score is greater than a set face image quality score threshold value or not; and the personnel verification module is used for carrying out face matching on the face images of the working site in the face images of the attributes of the training personnel on the construction site. According to the invention, association of constructor training and on-duty records is realized, identity verification is carried out during on-duty, and the safety guarantee level of a construction site is improved.

The application relates to a high-precision face matching method and system based on deep learning driving, sample data is collected and preprocessed, sample data pairs are expanded by a sample expansion model until preset conditions are met, the processed sample data pairs are normalized according to rules, the processed sample data pairs are input into a matching model for training, and the trained matching model is used for face matching; one or more image acquisition modules are used to acquire to-be-matched images, a preprocessing module is used to normalize the to-be-matched images according to the rules, a face feature extraction, matching and identification are performed on the face feature extraction, matching and identification by the face matching module, and a feedback module is used to feed back matching results. The application can orderly and efficiently expand a data set, reduce the training difficulty of a matching model, effectively train the recognition of synthetic photos and videos, improve the recognition accuracy and robustness, better prevent fraud attacks, be more suitable for security, access control and financial fields, have low computing resource demand, high real-time performance and guaranteed accuracy.

The embodiment of the invention discloses a contact person information generation method and head-mounted display equipment. A specific embodiment of the method comprises the following steps: controlling an image acquisition device to acquire a real scene image, and controlling a voice input device to acquire voice information; performing face detection processing on the real scene image to obtain at least one piece of face detection information; determining to-be-recognized face feature information according to each piece of face feature information included in the at least one piece of face detection information; performing face matching processing on the to-be-recognized face feature information and a preset face feature information set to obtain matching result information; determining first contact person information according to the matching result information; performing information extraction processing on each piece of collected voice information to obtain second contact person information; and generating contact person information according to the to-be-recognized face feature information, the first contact person information and the second contact person information. According to the embodiment, the convenience of recording the contact person information can be improved, and the user experience is improved.

This application discloses a voice assistant wake-up method, device, equipment, and storage medium, relating to the field of voice control technology. The disclosed voice assistant wake-up method includes: extracting vibration features based on vibration signals; matching the vibration features with a preset action library to obtain action matching degree and action matching timing information; determining a face matching score and an interaction environment score based on cockpit image data when the action matching degree is greater than or equal to a preset action matching threshold and the action matching timing information meets the corresponding preset action timing conditions; determining a voice assistant wake-up score based on the action matching degree, face matching score, and interaction environment score; and generating a voice assistant wake-up control command when the voice assistant wake-up score is greater than a preset threshold to wake up the voice assistant. This solution can achieve low-power and accurate wake-up of intelligent voice assistants in new energy vehicles.

The invention discloses a face recognition method and system of an intelligent lock with one-unlocking and multi-entry, and the method comprises the steps: extracting the face information and human body information of a multi-entry person in a snapshot time period; if the human face image and the human body image are extracted from the same person image at the same time, direct pairing succeeds; if the unique pairing relationship is determined through an exclusion method, the pairing is successful; the similarity of the human body information is calculated by retrieving the one-open multi-input track list, and if the similarity is larger than a preset threshold value, pairing succeeds; constructing a spatial-temporal trajectory sequence of the unretrieved and successfully paired human body information, and carrying out compatibility calculation on the spatial-temporal trajectory sequence and a human face clustering spatial-temporal trajectory sequence in a one-open multi-input trajectory list to determine a confidence coefficient; and fusing the pairing results, and for the face information corresponding to each piece of human body image information, taking the face information with the highest face matching confidence as a fusion result. By using the embodiment of the invention, the identification of the result of the multi-entry personnel with confidence can be constructed, and the identification of the multi-entry personnel is realized.

The present application provides an identity recognition method, device and equipment, and a storage medium, and relates to the technical field of biological recognition. The method comprises the following steps: obtaining a first face image and a first iris image of a first user; determining a plurality of first candidate identity identifiers of the first user and a face matching degree of each first candidate identity identifier with the first user according to the first face image; determining a plurality of second candidate identity identifiers of the first user and an iris matching degree of each second candidate identity identifier with the first user according to the first iris image; and determining a target identity identifier of the first user according to the plurality of first candidate identity identifiers, the plurality of second candidate identity identifiers, the face matching degree of each first candidate identity identifier with the first user, and the iris matching degree of each second candidate identity identifier with the first user. The method provided by the present application solves the problems of low recognition rate and low security when identity recognition is performed only by using face recognition.

A system of enhancing biometric analysis matching utilizes an image sensor, such as a digital camera, to capture an image of a face of a person. The system may perform image enhancement, such as edge and contrast enhancement, prior to performing face matching. The enhancement may be localized to a given image region based on determined region illumination. The system may perform image processing and analysis comprising face detection, alignment, feature extraction, and recognition. A biometric recognition confidence indicator may be generated using the results of the image enhancement and analysis. At least partly in response to the biometric recognition confidence indicator falling below a threshold enhancing recognition confidence using an image of visual indicia captured using the image sensor.

The embodiment of the invention provides a personal image digital human generation system, and the system comprises a facial feature extraction unit which is used for obtaining a facial image of a user, and carrying out the extraction of facial features from the facial image; the facial feature vectorization unit is used for vectorizing the extracted facial features to generate facial feature embedded vectors; the face matching unit is used for matching in a constructed digital human image library by using the face feature vector so as to screen a digital human image template matched with the user from the digital human image library; and the digital human generation unit is used for fusing the facial feature vector into the digital human image template so as to generate a personal image digital human for the user. By introducing the facial feature extraction unit, the facial feature vectorization unit, the facial matching unit and the digital human generation unit, automatic and precise conversion from the user facial image to the personalized digital human image is realized.

The invention discloses an intelligent navigation auxiliary method based on target detection, scene recognition and face matching. The intelligent navigation auxiliary method comprises the steps of video data acquisition, data preprocessing, target detection, scene recognition, face matching, reasoning optimization and voice feedback. And acquiring a real-time video stream in front of the user by using the head-mounted camera device, and transmitting the data to the mobile terminal device. According to the invention, through fusion of YOLOv5n target detection and MobilenetV3 scene recognition, accurate object detection and environment understanding are realized, and the cognitive ability of blind users to the surrounding environment is improved. The MTCNN is combined with the Facenet, and a multi-angle face database is combined, so that the recognition precision under complex illumination and posture changes is improved, and the social interaction ability of the user is enhanced. Based on NCNN reasoning optimization, the calculation resource consumption is reduced, the equipment end reasoning efficiency is improved, the efficient operation of the model on the mobile end equipment is realized, the endurance time is prolonged, and the user experience is improved.

The invention discloses a face data processing method and device, terminal equipment and a storage medium, and belongs to the field of face acquisition, and the method comprises the steps: obtaining a plurality of frames of three-dimensional image data acquired by a depth camera within a preset time, and determining a face region corresponding to each frame of three-dimensional image data; based on the face region of each frame, generating a face movement track within a preset time, and predicting the face movement track to obtain a face prediction track; judging the total duration based on the first duration of the human face movement track in the picture and the second duration of the human face prediction track in the picture; generating corresponding face processing data based on the judgment result, and performing face matching based on the corresponding face processing data; wherein the face processing data comprises one of a face feature vector or a super-resolution image. Therefore, by implementing the method and the device, the problem of low accuracy of a face acquisition technology in the prior art can be solved.

According to an embodiment of the present invention, a method for performing face recognition-based user authentication, the method being performed by a user terminal, may comprise the steps of: (a) capturing an image through a camera and recognizing a face of a user in the captured image; (b) providing a direction identifier at an random position in the image in consideration of the position of the recognized face in the image; (c) analyzing the captured image received in real time to determine whether a motion of the recognized face matches a command corresponding to the direction identifier; and (d) when it is determined that the motion of the recognized face corresponds to the command, changing the direction identifier, displaying same, and completing authentication, wherein at least one of the direction indicated by the direction identifier and the position at which the direction identifier is provided is randomly provided whenever authentication is performed.

A standalone digital display device that includes a visual sensor to capture images of a user's face and video scaler hardware controller executing a facial detection module to detect facial patterns of a user's face detected in front of the standalone digital display device in the captured images. The video scaler hardware controller to access the scaler storage device on the standalone display to determine if the detected facial patterns of the user's face match a facial pattern stored on the scaler storage device among a plurality of stored facial patterns. The video scaler hardware controller executes computer-readable program code of a profile bridging firmware module to, when a matching facial pattern is found, automatically apply user-selected on-screen display settings associated with the matched facial pattern independently from an operatively coupled information handling system to video data received from the operatively coupled information handling system for display of images.

The invention discloses a face feature recognition method and device based on multi-sensitive attribute privacy protection, and the device comprises a data receiving module which is used for receiving face data; the face image data preprocessing module is used for executing preprocessing operations such as alignment, cutting and standardization; the feature extraction module is used for performing feature extraction on the preprocessed face; the attribute extraction module is used for realizing privacy protection of sensitive attributes of the user face; the feature decoupling module is used for realizing that non-target attributes are not influenced when the target attributes are operated; the attribute decoding module is used for generating an image after privacy protection; the face matching module is used for keeping the identity recognition effectiveness of the face image after privacy protection; and the feature guiding module is used for realizing reversibility, that is, the generated image can be guided to generate an original image. And finally, the privacy protection device is deployed between the user and a third-party server, so that the user can protect the sensitive attribute privacy of the user while obtaining the corresponding service. The method can be widely applied to the field of privacy protection of face data.

The invention discloses a classroom attendance detection system and method based on intelligent identification, and relates to the technical field of classroom attendance detection. The classroom attendance detection method based on intelligent identification comprises the following steps: acquiring attendance image data in a set classroom, and performing target detection processing to obtain a plurality of student targets in the set classroom and corresponding area image data; analyzing the facial recognition confidence feature value of the corresponding student target, and judging whether the facial recognition confidence feature value is lower than a preset facial recognition confidence feature threshold value or not; if so, analyzing the posture matching ID of the corresponding student target based on a pre-trained posture recognition model; according to the method, attendance detection processing is carried out through the posture matching ID and the face matching ID of each student target, so that it is ensured that high recognition accuracy can be kept under the conditions of different illumination, postures and the like; therefore, the reliability of classroom attendance detection is obviously improved.

The invention provides a classroom attendance checking method based on face recognition, computer equipment and a storage medium, and the method comprises the following steps: matching a current classroom face feature with a preset face feature in a first face identity database to obtain a first face matching result; under the condition that the first face matching result is used for indicating that the identity identification corresponding to the face feature of the current classroom is not obtained through matching, matching the face feature of the current classroom with a real-time face feature in a second face identity database to obtain a second face matching result; the second face identity database is used for storing identities and real-time face features of a plurality of students; and under the condition that the second face matching result is used for indicating that the identity identifier corresponding to the face feature of the current classroom is obtained through matching, generating an attendance checking result corresponding to the current classroom period according to the second face matching result. According to the technical scheme, the identity label can be matched under the non-front-face postures of the student such as head measurement or head lowering so as to determine the identity of the student.