197 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.

There are described various embodiments for devices, systems, and methods for security threat detection and reaction using multi-layered decentralized federated learning approach, for use in various combinations of security systems, including facial recognition systems, biometric recognition systems, gesture recognition systems, voice recognition systems, network traffic pattern monitoring systems, security systems using Internet of Things (IoT) sensors, and home automation security systems. By combining federated learning system with a local interpretation layer, it is possible for each local node in a system to interpret anonymized federated learning results into highly personalized results, which can then be used to trigger highly personalized actions. The multi-layered federated learning threat detection and response system therefore optimizes for both enhanced privacy and customization.

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.

The invention provides a shield tunnel limited space safety operation protection early warning system and early warning method, and the system comprises RFID tags and Bluetooth positioning tags which are carried by shield tunnel operation constructors and are in one-to-one correspondence with the constructors; an identity management server; the environment monitoring system is provided with a plurality of sensor assemblies and is used for monitoring temperature, humidity and air quality in the tunnel; a Bluetooth beacon system; the UHF card reader and the face recognition system are arranged at the entrance of the shield tunnel; the environment safety early warning system carries out construction early warning according to the safety threshold range; a fingerprint database based on RSSI; the Bluetooth beacon positioning system is used for carrying out position estimation according to RSSI values of Bluetooth beacons located around the Bluetooth beacon positioning system scanned by the Bluetooth positioning tag and based on fingerprint data of a plurality of reference points in the fingerprint database, and determining the position of each constructor in the tunnel and the dynamic change of the position of each constructor; and the personnel safety early warning system is used for carrying out safety early warning based on the position and the change state of each construction personnel.

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 relates to the technical field of safety management, and particularly discloses a safety management system based on face recognition, which is used for solving the problem of insufficient cooperative processing of air conditioner airflow safety management and air return and exhaust utilization during arsine leakage in existing clean room airflow management. Comprising a photoetching production module, an air treatment set, a return air adjustment module, an arsine detection sensor, a face recognition system, an exhaust fan, a fresh air handling unit, five air return and exhaust channels, four air supply channels and an air discharge and recovery channel. An air return and exhaust adjustment scheme and a safe area air supply scheme are provided when arsine leaks; personnel permissions of areas with different cleanliness levels are managed through the face recognition technology, air supply of safe areas is adjusted in real time, negative pressure and air exhaust are automatically adjusted when arsine leakage occurs, the fresh air and return air mixing proportion is dynamically adjusted based on the air age, and air conditioner energy consumption is reduced.

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 discloses a robust semi-supervised multi-view face recognition system (RS2 Mv), and belongs to the field of face recognition. The method comprises the following steps: firstly, representing a collected face image through various types of features, and describing the face image from different feature levels; secondly, decomposing a feature matrix corresponding to each type of features into a pure data matrix and a noise matrix; then, learning self-representation subspaces corresponding to view angle features based on pure data obtained through decomposition; and finally, respectively optimizing each parameter through a coordinate descent method in an iterative optimization process until the system converges, and spreading label information of a labeled face image to a non-labeled face image through an image fused by the self-representation subspaces of multiple visual angles to complete face recognition. According to the method, the recognition precision of the face recognition system on the face image doped with noise data can be effectively improved, and accurate recognition of the non-label face image can be completed under the condition that only a small number of labeled face images exist.

The utility model discloses an intelligent goods shelf for preventing goods from being overweight, and relates to the technical field of intelligent goods shelf production, the intelligent goods shelf comprises a base and a placing groove, an auxiliary mechanism is arranged in the placing groove, and the auxiliary mechanism comprises a bottom plate movably connected to the bottom position of the placing groove and a movable plate at the top position of the bottom plate; a screw rod is fixedly connected to the interior of the movable plate, a crossed supporting rod is arranged outside the screw rod, a standing plate is fixedly connected to the top end of the crossed supporting rod, sliding blocks on the two sides of the bottom plate are slidably connected with sliding grooves of the containing grooves, and a nut base is movably connected to the interior of the movable plate and is in threaded connection with the screw rod; the crossed supporting rod is driven by the screw rod to ascend and descend to a proper height. Compared with an existing common intelligent goods shelf, the intelligent goods shelf capable of preventing the goods from being overweight has the advantages that all goods information and storing and taking conditions of a user can be checked through the face recognition system, the user can conveniently and rapidly take the goods, and the goods taking convenience of the user 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 utility model discloses a work clothes distribution cabinet with a recognition function, relates to the technical field of work clothes distribution cabinets, and aims to solve the problems that pedestrians often pass through a doorway of an existing distribution cabinet, so that a face recognition system frequently verifies the passing pedestrians, errors of the recognition system are easily caused, and electric power is wasted. Comprising a distribution cabinet body; the distribution cabinet comprises a distribution cabinet body and further comprises a plurality of containing bins, the containing bins are integrally formed in the distribution cabinet body, the containing bins are evenly distributed in the distribution cabinet body, cabinet doors are arranged at the front end of the distribution cabinet body, and the cabinet doors are arranged at the front ends of the containing bins through connecting pieces and can be opened and closed; an identification camera is arranged above the front end of the cabinet door, an illuminating lamp is arranged outside the camera, a door lock is arranged on one side of the front end of the cabinet door, the input end of the identification camera is electrically connected with the output end of the door lock, and a sliding rail is arranged on the surface of the front end of the cabinet door.

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 frequency spectrum recognition model training method in a black box decision attack scene, which belongs to the field of face recognition processing and is characterized in that an attack target function is efficiently optimized by evolutionary attack by querying a black box model based on the given attack target function. According to the method, the local geometric structure in the search direction is modeled in the black box decision attack process, and the dimension of the search space is reduced, so that the query efficiency of the black box model is improved. Experimental results verify the effectiveness of the evolutionary attack method, and compared with a reference method, the evolutionary attack method can generate an adversarial sample with smaller disturbance through fewer model query times. According to the invention, an evolutionary attack method is further applied to break through a commercial face recognition system, which shows that the method has good practicability.

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 invention discloses an anti-congestion face recognition gate for a security check channel, and relates to the technical field of gates. The device comprises two box bodies and swing gate mechanisms installed on the two box bodies. By adopting the linkage design of the shunting mechanism and the trigger plate, when a worker steps on the trigger plate through the shunting mechanism, the movement of the shunting mechanism can be limited through the trigger plate, and workers behind are prevented from advancing, so that a detection section which is not influenced by other workers can be formed between the swing gate mechanism and the shunting mechanism; therefore, the influence of external factors on the face recognition device is reduced, it can be guaranteed that the face recognition device can operate at a high speed, worker information is effectively recognized, and workers are not prone to congestion at the position; a worker can carry out online registration by pressing a shooting button and open a gate mechanism to enter the construction site through the security booth, so that the congestion phenomenon is reduced.