137 results about "Facial recognition system" patented technology

The present invention provides a facial recognition system using deep learning methodologies while integrating privacy-preserving capabilities. This system employs convolutional neural networks (CNNs) to extract and classify facial features, ensuring high accuracy in recognition tasks. Moreover, the system addresses privacy concerns by incorporating techniques such as facial feature encryption and anonymization, thereby enhancing user privacy and data security. This invention is applicable across various domains, including security, surveillance, access control, and personalized services, where facial recognition is utilized while preserving individual privacy.

The invention discloses a power transmission line constructor identity verification method based on face recognition, and relates to the technical field of electric power engineering safety management, and the method comprises the steps: collecting multispectral face data, and generating a spectral stereo feature matrix; micro blood flow pulsation characteristics, skin texture characteristics and thermal imaging temperature distribution characteristics are extracted from the spectrum stereo characteristic matrix, a three-layer cascade anti-counterfeiting verification mechanism is constructed, and comprehensive living body judgment is carried out; establishing a distributed feature matching network, and matching the spectrum stereo feature matrix with a pre-stored feature library; collecting a geographic position track and an operation behavior mode of a constructor, and carrying out multi-dimensional cross validation on the geographic position track and the operation behavior mode and an identity matching result to generate a multi-level safety evaluation index; and writing the identity verification process and the multi-level security evaluation index into a distributed account book, and generating a verification voucher. According to the invention, cross analysis is carried out on the identity matching result of the constructor and the behavior characteristics, so that the problem that a traditional face recognition system is easily falsely used by the identity is effectively solved.

According to the face data privacy protection method and device provided by the embodiment of the invention, a credible authority management mechanism is constructed through a distributed network and a smart contract, and a multi-dimensional feature extraction scheme fusing geometric features and texture features is innovatively designed. The system adopts data fragmentation and homomorphic encryption technologies to carry out security processing on feature vectors, and dispersedly stores encrypted data in a block chain network, so that decentralized management of the feature data is realized. According to the method, feature comparison and identity verification are carried out in a ciphertext domain, the whole process is traceable in combination with a timestamp and an operation record, the problems of data security and privacy protection in a traditional face recognition system are effectively solved, and a safe and credible technical solution is provided for the field of biological feature recognition.

The invention discloses a face recognition system based on computer vision and an application method thereof, and relates to the technical field of face recognition. The system comprises a fine-grained shielding classification module, a multi-modal feature fusion module, a cross-modal confrontation identification module and a compensation verification module. By analyzing the depth data and the polarized light parameters, an occlusion thermodynamic diagram is generated, and an identifiable area and an occlusion area are marked. And according to the occlusion label of the thermodynamic diagram, activating infrared and sonic sensor data, extracting the relevance between the temperature change and the vibration frequency, and generating a facial occlusion area feature map. And calculating the similarity between the sheltered region feature map and the non-sheltered region feature, and detecting a forgery attack. And analyzing the difference rate of adjacent frames through a sliding window, marking compensation distortion, rejecting low-credibility data in combination with confidence and attack marks, and outputting a complete facial feature vector and a risk level. And the recognition accuracy and the system security in a complex environment are remarkably improved.

The invention discloses a user privacy protection method and device for a face recognition system, and belongs to the technical field of mobile equipment and software security, and the method comprises the steps: carrying out the edge detection and lightweight semantic segmentation parallel processing of an input image, and generating edge strength mapping and semantic confidence mapping; generating a privacy grading mask through dynamic weight fusion edge strength mapping and semantic confidence mapping; dividing the image into three levels of privacy areas through a privacy grading mask; performing hierarchical encryption on the three-level privacy area through three non-periodic chaos sequences generated in advance to complete user privacy protection; wherein the three non-periodic chaotic sequences are iteratively generated through a Young's hyperchaotic system based on a Hash value spliced by a user-defined key and system time; according to the invention, picture encryption according to the privacy level is realized, and the user privacy in face recognition is protected.

A computerized method of generating training and / or testing data for a face recognition machine learning network applied by a face recognition system is presented. The method comprises defining a semantic parameter space, wherein the semantic parameter space comprises a vector of semantic parameters associated with a facial image. The method further comprises training a mapping machine learning network to transform the vector of semantic parameters to a vector of style space parameters of a style-based generative adversarial network. When the mapping machine learning network is trained, the method further comprises generating a variation vector of style space parameters for an input facial image by applying the trained mapping machine learning network and feeding the style-based generative adversarial network with the variation vector of style space parameters to generate a variation facial image for the input facial image. Finally, the method comprises storing the variation facial image in a database and training and / or testing the face recognition machine learning network at the face recognition system by using a plurality of variation facial images stored in the database. A corresponding face recognition system and a computer program are provided, too.

The invention discloses an electronic license technology for special operation examination and approval through material object scanning and face recognition, and particularly relates to an electronic operation license for examining and approving dangerous operation for special operation in a production field in an information acquisition and online management mode. Comprising a special operation management and control system, a face / appliance recognition system, a gas detection system and a movable monitor. According to the special operation management and control system, an informatization platform is mainly built, the original paper version approval process is converted into online approval, whole-process supervision is achieved, and meanwhile a mobile phone end APP and a computer end webpage are built. The face / appliance recognition system is mainly used for a face recognition system and an equipment and facility recognition system; the gas detection system comprises a portable gas concentration detection alarm instrument, a data storage device, a data transmission device and a recording device; the movable monitoring system can construct all processes for monitoring, remote supervision is facilitated, and archiving and reviewing are achieved at the same time. An informatization centralized management and control mode is adopted, the original tedious processes of paper version approval, archiving, regular detection of toxic and harmful gases and recording are broken through, online approval and process full recording are realized through system construction, a tamper-proof function is set, the record traceability is ensured, real field confirmation of personnel at all levels is ensured, and the system is safe and reliable. And meanwhile, the whole process can be remotely and comprehensively monitored.

Face recognition systems are vulnerable to the presentation of spoofed faces, which may be presented to face recognition systems, for example, by an unauthorized user seeking to gain access to a protected resource. A face liveness detection method that addresses this vulnerability utilizes motion analysis to compare the relative movement among three regions of interest in a facial image and based upon that comparison to make a face liveness determination.

Describes the use of multimodal facial attributes in a facial recognition system. Additionally, the use of one or more auxiliary attributes, such as temporal attributes, can be combined with visual information to improve the facial recognition performance of the facial recognition system. In some examples, the use of multimodal facial attributes in a facial recognition system can be combined with the use of one or more auxiliary attributes, such as temporal attributes. Each of these techniques can improve the verification performance of the facial recognition system.

A face identification system, and a non-transitory computer readable medium with instructions, that when executed, perform a method for identifying a face image are described. The face identification system comprises a camera for facial image capture, encryption circuitry for image encryption, feature extraction circuitry for processing encrypted images, a face recognition system for identification, and an identification notifying system for result transmission. The encryption circuitry includes a pixel-bit converter, transforming pixel intensities into binary digits, and a 2D cellular automata function, working with a 3×3 matrix of binary-state cells transitioning by update rules. A gray code generator maps binary numbers to unique gray-scale values. The system integrates advanced encryption techniques with efficient feature extraction and recognition algorithms, addressing challenges in biometric authentication. This approach enhances security, accuracy, and computational efficiency compared to conventional systems, making it suitable for various applications requiring secure and efficient facial recognition.

The present disclosure relates generally to identifying subjects based on correlated family relation (e.g., kinship) characteristics. Using the present techniques, a facial photo of a subject, suspected to be a grown-up missing child, or any other person who may or may not have undergone changes in their appearance, is presented. Regular facial recognition systems cannot find the subject because the photo is not in any database (and because only family member photos may be in the database, and / or the photo may be a past photo of the subject in which the subject looks significantly different). With change-agnostic family matching, the facial photo of the subject is matched with the closest family signature(s), such that a relevant family or families may be identified. Possible family matches are presented in descending order where the closest families are presented first.

The invention discloses a stranger face recognition system and method, a foot-type humanoid robot and a medium, which are applied to the technical field of image processing, and adopt a multi-task face recognition model to perform face bounding box prediction and face key point extraction on an environment image to obtain a face key point set in each face bounding box; aligning the face key point set in each face bounding box to the standard template face image to obtain an undeformed face image; extracting a face feature vector of a to-be-recognized face from each non-deformation face image; calculating the similarity between the face feature vector of each face to be recognized and the face feature vector of each temporary reference face in a lightweight face database; and determining whether the to-be-recognized face is a stranger face based on the similarity. Thus, stranger face recognition can be achieved on the foot type humanoid robot, network delay caused by cloud comparison is avoided, real-time interaction response in a public environment is achieved, and the man-machine interaction efficiency is improved.

The invention belongs to the technical field of automatic luggage storage and taking, and particularly relates to an internet-based automatic luggage storage and taking safety optimization system, which comprises a safety transmission and pickup module, a luggage cabinet distribution module and a cabinet capacity arrangement module. According to the scheme, the passenger priority, the path cost and the cabinet vacancy rate are combined, the nearest and load-balanced cabinets are dynamically allocated through the deep Q network, the luggage access cost of passengers is reduced, the historical luggage size and time interval distribution are analyzed, the cabinet size proportion strategy table is generated, the storage cabinets are monitored in real time, personnel are dispatched in time, and the storage cabinets are quickly added. The peak demand is met; the defects of a traditional face recognition system are effectively overcome through multi-modal security authentication and a dynamic optimization mechanism, single face recognition is replaced with two-factor authentication combining OTP passwords and biological characteristics, and recognition failure caused by strong light and shielding is avoided.

There is provided an information processing apparatus, an information processing method, and a program that allow for reduction in power consumption in authentication using multiple cameras. The information processing device performs camera search processing of searching for a camera suitable for authentication of a target among non-activated cameras yet to be activated, on the basis of a position and an angle of the target estimated from an image captured by an active camera which is an activated camera among multiple cameras, and activating the camera found by the search. The present technology can be applied to facial recognition systems.

The utility model provides a shield tunnel limited space safety operation protection early warning system, comprising RFID tags carried by constructors and corresponding to the constructors one by one; an identity management server; the environment monitoring system is provided with a plurality of sensor assemblies and used for monitoring the temperature, humidity and air quality in the limited space of the shield tunnel; the UHF card reader is arranged at the entrance of the shield tunnel and used for preliminarily positioning the identity of a constructor; the face recognition system is used for carrying out face image acquisition and face recognition and registration on the entering constructors and counting the total number of the constructors; the environment safety early warning system is used for receiving the temperature, the humidity and the air quality which are monitored in real time and performing construction early warning according to a safety threshold range; and the monitoring center is connected with the identity management server, the face recognition system and the environment safety early warning system, is provided with a display screen, and is used for displaying data monitored by the environment monitoring system and early warning information.

The invention discloses a training scheme and system for improving the ability of a face recognition model. A feature space boundary threshold value t is calculated, a function LFeasibleFace capable of meeting the face loss is constructed, dissimilar sample gradients are filtered, and stable convergence of the model is achieved. According to the scheme, a dynamic learning rate strategy is adopted, a Softmax function is not needed, GPU communication is reduced, and the training efficiency is improved. Experiments show that the scheme is superior to a mainstream method in recognition precision on multiple test sets, the training speed is improved by 2%, and the scheme is suitable for face recognition system optimization in scenes such as security and protection and finance.

The invention relates to a multi-mode intelligent security check system, which comprises an application auditing system, a security check channel system and a monitoring system, wherein the security check channel system is provided with an alarm mechanism; the monitoring system is used for monitoring the application auditing system and the security check channel system; the security check channel system comprises a vehicle security check channel and a personnel security check channel which are provided with A and B doors and transmit information to the monitoring system, the vehicle security check channel is provided with a life detection system, a vehicle bottom scanning system and a vehicle driver checking system, and the personnel security check channel is provided with an article detection and storage system and a multi-stage second non-inductive face recognition system; the monitoring system comprises a police officer monitoring unit, an armed police monitoring unit and a remote monitoring unit which are all provided with monitoring terminals. The monitoring terminals monitor the application auditing system and the security check channel system and give out corresponding instructions when abnormity is found according to received information. According to the invention, safe and efficient security check can be realized, information synchronization of multiple departments is realized, and the working efficiency is improved.

The invention provides a staff image matching and archiving method and system based on face recognition, and relates to the technical field of archive management. The method comprises the following steps: calculating the similarity of face features of known employees and forming a to-be-detected image set; collecting multi-source auxiliary information and carrying out multi-dimensional analysis on the multi-source auxiliary information for known employees with identity splitting conditions, and constructing an evidence chain; according to an analysis result of each dimension in the evidence chain, calculating a file merging confidence coefficient of the to-be-verified image file; if the file merging confidence coefficient is greater than or equal to a preset merging threshold value, merging the to-be-verified image file into a real image file of the corresponding known staff; otherwise, early warning information is generated and submitted for manual auditing. The method aims at solving the technical problem that a traditional face recognition system is prone to cause identity splitting in a complex environment, automatic and accurate filing of staff image files is achieved, manual intervention requirements are reduced, and file management efficiency and data quality are remarkably improved.

The utility model relates to the technical field of management cabinets, and discloses an intelligent cutter management cabinet which comprises a cabinet body, an installation groove and a sliding groove are formed in the cabinet body, a door plate is fixedly installed on the outer side of a connecting shaft, and a face recognition system and keys are fixedly installed on the surface of the door plate. According to the utility model, the face recognition system and the keys are fixedly mounted in the door plate, and the keys are electrically connected with the electronic lock assembly in the door plate, so that when a cutter needs to be taken to process a lens, an identity card or a mobile phone number needs to be input through the keys, and then the door plate is opened; and meanwhile, a human face input in advance is compared and recognized through a human face recognition system, after the comparison and recognition are passed, the electronic lock assembly is unlocked, the door plate can be conveniently opened through the rotating action of a connecting shaft and a second fixing block, and therefore practical authentication is achieved, and the situation that the cost is increased due to the fact that the cutter is lost after being taken away is prevented.

The invention provides a preparation method of a charging pile electronic lock motor, which comprises the following steps: S1, preparing a micromotor and a reduction gearbox, and arranging an absolute value encoder at the output end of the micromotor; s2, providing a high-definition pinhole camera device, and preparing a face recognition system and / or a fingerprint recognition system; s3, a main control circuit board communicating with the cloud server is prepared, data transmitted by the face recognition system and / or the fingerprint recognition system is sent to the user intelligent mobile terminal, the user intelligent mobile terminal can carry out charging confirmation according to the received sent data and a power supply access signal transmitted by the vehicle-mounted computer, a confirmation signal is formed, and charging is carried out according to the confirmation signal. And the cloud server receives the confirmation signal sent by the household intelligent mobile terminal and sends a formal charging start signal to the charging pile. The intelligent charging gun comprises the intelligent motor prepared by the method, and the stability and the reliability of charging connection and the effectiveness and the accuracy of billing are improved.

The invention discloses a knowledge migration method and system for rapid updating of a face recognition system, and the method transfers knowledge obtained by an old-version face recognition model to a new-version face recognition model through a secondary knowledge distillation mode, thereby achieving the great reduction of the training time, and guaranteeing the rapid updating of the face recognition system.

The invention belongs to the technical field of face recognition, and particularly discloses a multi-dimensional feature-based face recognition method and system and a program product, and the method comprises the steps: collecting a face image of a target object, carrying out the enhancement processing, obtaining an enhanced face image, carrying out the feature extraction of three dimensions, i.e., gray scale features, texture features and contour features, based on the enhanced face image, and obtaining a face recognition result. And then determining the similarity between the face image of the target object and the corresponding face image sample in the database under the three-dimensional features, and finally judging the face recognition result of the target object based on the weighted summation similarity, so that accurate and efficient face recognition can be realized. According to the invention, through the face recognition process in combination with multi-dimensional feature analysis, the limitation of single feature dimension face recognition can be effectively solved, the accuracy and robustness of face recognition are improved, and the reliability of a corresponding face recognition system is improved.

The present application discloses a face recognition method, device, and computer-readable storage medium, which relate to the field of image processing technology. The method comprises: inputting a face image into a face feature extraction network to extract features and obtain intermediate layer features and face features; discretizing the intermediate layer features to obtain a discretization result; masking the discretization result to obtain a masked result, and inputting the masked result into a preset prediction network for prediction to obtain a prediction result; calculating the confidence level corresponding to the face image based on the discretization result and the prediction result, wherein the smaller the difference between the discretization result and the prediction result, the greater the confidence level; and performing face recognition based on the confidence level corresponding to the face image and the face features. The present application provides a face recognition solution to avoid the situation where the face recognition algorithm produces erroneous recognition results and improve the overall effect of the face recognition system.

Face recognition method comprising, in an enrollment phase, capturing a biometric feature e.g. face of user / s uE, and / or extracting therefrom a biometric template for the user, and / or extracting a hash-value from the template and / or deriving a value more stable and / or more deterministic and / or less noisy than the template; and / or hashing and / or saving this value e.g. as hashed and / or subsequently processing a user uL alleging s / he is uE by comparing this value as saved to a value derived from a biometric feature e.g. face captured from user uL.

This application discloses a face recognition method, a face recognition system, a terminal device, and a storage medium. The face recognition method includes: acquiring a face image to be recognized and extracting initial face features corresponding to the face image; secretly segmenting the initial face features to obtain at least a first face feature to be recognized and a second face feature to be recognized; determining a first difference between the first face feature to be recognized and a plurality of first reference face features in a first server, and determining a second difference between the second face feature to be recognized and a plurality of second reference face features in a second server; the first and second reference face features are obtained by secretly segmenting reference face features corresponding to reference face images; and obtaining a recognition result corresponding to the face image to be recognized based on the first and second differences. The face recognition method of this application stores the segmented face features on different servers for computation, reducing the risk of face feature leakage.

This invention provides a method for manufacturing an electronic lock motor for a charging pile, comprising: S1 manufacturing a micro motor and a reduction gearbox, and setting an absolute encoder at the output end of the micro motor; S2 providing a high-definition pinhole camera device, and manufacturing a face recognition system and / or a fingerprint recognition system; S3 manufacturing a main control circuit board that communicates with a cloud server, and sending data from the face recognition system and / or fingerprint recognition system to a user's smart mobile terminal. The user's smart mobile terminal can confirm charging based on the received data and the power access signal from the vehicle computer, forming a confirmation signal. The cloud server then receives the confirmation signal from the user's smart mobile terminal and sends a formal charging start signal to the charging pile. The smart charging gun includes a smart motor manufactured using the above method, improving the stability, reliability, billing effectiveness, and accuracy of the charging connection.

To provide a verification device, a verification system, and a verification method capable of improving a processing speed of verification using facial images of people passing through a specific region.SOLUTION: In a facial recognition system, a verification device for regulating the flow of people includes: a processing unit that performs second facial image verification by using a first candidate facial image narrowed down from a plurality of facial images included in a facial image database and a facial image included in second images obtained by imaging a second region on the basis of the result of first facial image verification using facial images included in first images obtained by imaging a first region and the plurality of facial images included in the facial image database in a route where there is a flow of people moving from the first region to the second region located upstream of a position where the flow of people should be regulated; and a communication unit that outputs the result of the second facial image verification.SELECTED DRAWING: Figure 3

The present invention provides a facial recognition system for alleviating ambient light during image capture, the system comprising: - a stereo camera configured to capture an image and send it to a face detection module, wherein the image comprises depth information of objects within the depth of field, - the face detection module configured to identify a face based on the depth information of the received image from the stereo camera, - an processing module configured to - split the image into a facial area and a non-facial area, wherein the facial area corresponds to the identified face region by the face detection module, and - outcome exposure adjustment factors for each area, these exposure adjustment factors being calculated based at least on a brightness values comparison of both facial and non-facial areas, - a dual-regional adjustment module configured to separately adjust the exposure of both the facial and non-facial areas according to the adjustment factors, and - a face matching module configure to verify or enroll person's face identity based on the exposure-adjusted facial area.

The application relates to the field of face recognition applications, in particular to a face recognition system and method based on a door lock and ensuring data security, which comprises a collection end S1, a camera module S11, a face algorithm module S12 and a network transmission module S13; the camera module S11 comprises a plurality of cameras in different directions; the face algorithm module S12 is used for image scanning and judgment of local image information in all directions and extraction of local feature data; and the network transmission module S13 is used for encryption, packaging, labeling and transmission of all local feature data; the application provides a face recognition system and method based on a door lock and ensuring data security, different parts of a face are recognized through a plurality of cameras contained in the collection end, thereby controlling extraction of feature quantity, distinguishing and protecting features, preventing face data from being read, and realizing safety control of face data in face recognition of a door lock.

The present application provides a method, apparatus, device, and storage medium for generating adversarial samples for a face recognition model, and relates to the field of face recognition in artificial intelligence technology. After acquiring an attacking face image and a target face image, the embodiment of the present application obtains an attribute noise vector based on the attacking face image, and edits the true face attribute vector based on the attribute noise vector to obtain a first attribute vector. The attributes of the attacking face image are then edited based on the first attribute vector to generate an adversarial sample of the target face image. The method of the embodiment of the present application can help improve the concealment of adversarial noise in adversarial samples, and thus can help improve the security of face recognition systems.