96 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 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.

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 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.

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.

The invention discloses a face recognition method based on a face expert hybrid model and application, and belongs to the technical field of computer vision. According to the face recognition method based on the face expert hybrid model, firstly, a data set and a data enhancement strategy are utilized to train a plurality of face recognition networks, so that the face recognition networks are adaptive to different complex scenes; then, constructing a face expert hybrid model comprising a shared expert network, a routing expert network and a dynamic gating network, and screening the activated expert network through the dynamic gating network to obtain an optimal face feature vector; then introducing a complementary auxiliary loss function to prevent model collapse caused by extreme imbalance of expert load in the training process; finally, reasoning is conducted in a sparse activation mode, and calculation expenditure is reduced. The method can significantly improve the generalization ability of face recognition in different ages, shielding and illumination scenes, optimizes the training reasoning efficiency and model stability, and can be widely applied to various face recognition systems.

The invention relates to a method for improving the wearing rate of a reflective vest and the carrying rate of necessary articles for constructors, which comprises the following steps of: fixing a first part of a split RFID (Radio Frequency Identification) tag at a design position on the reflective vest, and pre-inputting personal identification information of the constructors to a second part of the split RFID tag and holding the second part of the split RFID tag by the constructors, a conventional RFID tag is arranged on each necessary article, article category identification information is recorded in advance, personal identification information is recorded in the bracelet in advance, a split RFID reader and a face recognition system are installed at the entrance guard of a construction site, a background control system reads the personal identification information of the reflective vest through the RFID reader, and the reflective vest is used for identifying the personal identification information of the reflective vest through the face recognition system. If the information is checked to be the same person through the face recognition system, the person is released; in a construction site, the split RFID tag, the conventional RFID tag and a bracelet worn by a constructor are linked, whether the split RFID tag on the reflective vest is in a normal state or not is determined, and whether an entering person carries a necessary article or not is determined.

The invention discloses a face recognition system switch with an interface switching function, and relates to the technical field of switches, the face recognition system switch comprises a switch body and a connecting frame, the front surface of the switch body is provided with a network port and an optical port, the front surface of the switch body is provided with a storage groove, and the storage groove is provided with an interface. Heat dissipation fins are mounted on the upper surface of the switch body; a connecting frame is installed on the right side of the switch body, and connecting blocks are installed on the front side and the rear side of the filter screen. According to the switch with the interface switching function for the face recognition system, a filter screen on a connecting frame can be quickly disassembled and assembled through a guide strip and a sliding groove, and a cleaning brush assembly can be driven to clean through a second rotating mechanism without disassembly; during cleaning, the position of the brush body is fixed through the limiting bolt, the filter screen is pushed to move through the pushing handle, efficient dust removal is achieved, the filter screen is convenient to disassemble and clean, the tedious problem that a traditional filter screen depends on manual disassembly and cleaning is solved, and the operation and maintenance requirements of large-scale deployment are met.

The invention relates to a method for realizing face recognition confrontation sample generation based on frequency domain decomposition and an attention mechanism, and the method comprises the following steps: carrying out the data preprocessing, and carrying out the model construction; generating an attention mask M; performing frequency domain decomposition by using a discrete wavelet transform algorithm; constructing a joint loss function J; frequency domain disturbance iterative optimization is carried out, and disturbance variables are initialized in a frequency domain space; and repeating until an attack stop condition is met, and outputting a final confrontation sample image. The method, the system, the device, the processor and the computer readable storage medium for generating the face recognition adversarial sample based on the frequency domain decomposition and the attention mechanism have the advantages of high mobility, high concealment and high robustness, and the adversarial sample generated based on the frequency domain has higher resistance to common image processing operation; the algorithm is universal, and the proposed framework does not depend on a specific model structure and can be flexibly applied to various CNN-based face recognition systems.

A method of determining an operating status of one or more hardware components of a facial recognition system of a mobile device includes engaging the facial recognition system of the mobile device, wherein the facial recognition system comprises a dot projector and an infrared ("IR") camera; capturing an image of the dot projector and the IR camera; comparing the captured image to a predetermined test image; and based on the results of the comparison, determining the operating status of at least one of the dot projector and the IR camera.

The application 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, adopt a multi-task face recognition model, perform face boundary frame prediction and face key point extraction on an environment image to obtain a face key point set in each face boundary frame, align the face key point set in each face boundary frame to a standard template face image to obtain a non-distortion face image, extract a face feature vector of a face to be recognized from each non-distortion face image, calculate 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 determine whether the face to be recognized is a stranger face based on the similarity. In this way, stranger face recognition can be realized on the foot type humanoid robot, network delay caused by cloud comparison is avoided, real-time interaction response in a public environment is realized, and human-computer interaction efficiency is improved.

The invention provides a pharmacy window business integrated system and method based on an intelligent tracing identification technology, and the technology integrates the functions of drug tracing code automatic identification, pharmacy business process optimization, multi-system data collaboration, intelligent early warning and the like. And a biological recognition technology (such as a face recognition system) is integrated aiming at a receiving link of special management medicines (such as anesthetic medicines and mental medicines), so that intelligent, automatic and full-process tracing management of pharmacy window services is realized. The invention belongs to the technical field of cross application of hospital informatization management and an intelligent identification technology, and relates to deep fusion of medical compliance supervision and biological feature identification.

The present application provides a face recognition presentation attack detection system, and relates to the technical field of face recognition security. The system can receive a user's face recognition request through a face image information acquisition front end, and simultaneously acquire 3D face information, living body information, and environmental information, and other multi-dimensional face image information. More complex face data can be acquired. After face security detection and recognition, the multi-dimensional face image information is subjected to abnormal detection and filtering processing, which can effectively prevent model data poisoning attacks. When face recognition is performed based on multi-dimensional face image information, the called face recognition model is subjected to black box detection and white box detection for security detection, which can verify the correctness of the model, prevent the model from being used incorrectly or stolen and changed by attackers, cracked and used to cheat and attack the system, and improve the security of the face recognition model. The system monitoring module performs security monitoring and management on the life cycle of face recognition, further ensuring the security of the face recognition system.

This invention relates to a method, apparatus, readable storage medium, and electronic device for detecting anomalies in face recognition. It can determine the comprehensive attention features of a captured face image and the comprehensive attention features of a face image without interference features, and based on the difference in the distribution of activation values ​​of these two comprehensive attention features in the face recognition model, determine whether the captured face image is an image maliciously constructed by an attacker, thereby detecting the occurrence of anomalies caused by an attacker and improving the security of the face recognition system.

To allow for preventing double registration of face information of a user for use in face authentication.SOLUTION: A face authentication server 2 acquires face information of a user as first face information for collation from a user terminal 3, and executes first collation processing of collating the first face information for collation with a plurality of pieces of registered face information stored in a storage device 13 to calculate collation scores indicating similarity between the first face information for collation and the registered face information. If a collation score equal to or higher than a prescribed threshold is calculated in the first collation processing, the server causes the user terminal 3 to display a registering operation screen 66 for prompting the user to execute an operation of registering the face information of the user, wherein the registering operation screen 66 includes alert information showing that the face information of the user has been registered, and when the operation of registering the face information of the user is executed on the registering operation screen 66, the face information of the user is stored in the storage device as the registered face information.SELECTED DRAWING: Figure 5

An object of the present invention is to provide a technology that enables appropriate authentication processing for online learning. [Solution] In order to solve the above problems, the present invention provides a face authentication system for performing face authentication on students taking online learning courses, the face authentication system comprising a database, an acquisition unit, a tracking processing unit, and an authentication processing unit, the database stores authentication face information for authenticating the students, the acquisition unit acquires face information of the students while they are taking the displayed online learning course, the tracking processing unit performs face tracking processing based on the face information, and the authentication processing unit performs authentication processing based on the face information for which the face tracking processing was successful and the authentication face information.