50results about How to "Improve the efficiency of face recognition" patented technology

The present disclosure relates to a video processing method and apparatus. The method comprises: locating a face image in a detection frame by performing face detection on the detection frame in a to-be-processed target video; performing face tracking on a track frame in the to-be-processed target video based on face information obtained through detection, to determine face information comprised in the track frame; and extracting the detection frame and track frame comprising the face information from the target video, performing face recognition on an extracted to-be-recognized frame image based on a recognition model that is acquired in advance, and performing screening on a recognition result, to acquire a final face recognition result. Therefore, the final face recognition result is displayed to a user, to prompt the user actor information appeared in the video. According to the video processing method, face recognition efficiency is effectively improved.

The embodiments of the present invention provide a face recognition system and method. The system is deployed on a cloud platform. The system includes a load balancing server, an application service cluster and a face recognition cluster; the load balancing server is used for selecting a target application server, sending an obtained target face recognition request to the target application server and receiving a result acquisition request sent by the target application server; a target face recognition server is selected, and the result acquisition request is forwarded to the target face recognition server; the target application server is used for receiving the target face recognition request, obtaining information to be identified according to information to be processed carried in the target face recognition request; the result acquisition request is sent to the load balancing server; the target face recognition server is used for receiving the result acquisition request forwarded by the load balancing server; face recognition is performed on a source image; and a face recognition result is sent to the initiator of the result acquisition request. With the face recognition system and method provided by the embodiments of the present invention adopted, face recognition efficiency is improved.

The invention discloses an anti-deception three-dimensional face recognition method based on information fusion. The anti-deception three-dimensional face recognition method comprises: 1, collecting and processing color images and depth images of a plurality of real faces; 2, establishing Gaussian distribution models of a plurality of real faces according to the depth information of the key pointsin each depth map, and determining a threshold range of Gaussian distribution parameters of the real faces; 3, establishing a Gaussian distribution model of the to-be-recognized face, comparing and judging the Gaussian distribution model parameters of the to-be-recognized face with the threshold range of the Gaussian distribution parameters of the real faces, if the to-be-recognized face is judged to be the real face, executing the step 4, and otherwise, not performing face recognition; 4, constructing a deep convolutional neural network and training the deep convolutional neural network; and5, inputting the to-be-recognized face image into the trained deep convolutional neural network for recognition, and outputting a recognition result. By analyzing and modeling the face depth information and fusing the face depth information at the data end, a lightweight network is constructed, and the performance of the whole face recognition system is improved.

The invention discloses an express cabinet pickup method and device, an express cabinet and a storage medium. The method comprises the following steps: acquiring user identification information of anexpress item, and sending the user identification information to a server, wherein the user identification information is used by the server to determine a user image download link corresponding to the express item; receiving the user image download link fed back by the server, acquiring a user image corresponding to the express item according to the user image download link, and saving the user image to a local image database; when a pickup instruction is detected, acquiring a user image of a current user, and matching the user image of the current user with the user image in the local imagedatabase; and processing the pickup instruction according to a matching result and a preset pickup condition. Through adoption of the express cabinet pickup method and device in the embodiment of theinvention, face recognition can be finished locally by means of the computing power of each express cabinet without the need of interacting with the server through a network, thereby improving the face recognition efficiency and the pickup speed, and improving the user experience.

The invention relates to car door unlocking methods and device, a system, a car, electronic equipment and memory media. A method comprises the steps of searching Bluetooth equipment of a preset identity through utilization of a Bluetooth module set on the car; in response to the fact that the Bluetooth equipment of the preset identity is searched, establishing Bluetooth pairing connection betweenthe Bluetooth module and the Bluetooth equipment of the preset identity; in response to the fact that the Bluetooth pairing connection is successful, waking up and controlling an image collection module set on the car to collect a first image of a target object; carrying out face identification based on the first image; and in response to the fact that the face identification is successful, sending a car door unlocking instruction to at least one car door of the car. According to the embodiments of the invention, requirements for low power operation, rapid opening of the car door and improvement of user experience can be satisfied.

The invention relates to a face recognition method and system, and relates to the technical field of information, wherein the face recognition method and system mainly aim at completing face recognition through the smaller calculation amount compared with the prior art. The method includes the steps of clustering collected face images to obtain multiple first-layer classifications, continuing clustering face images in at least one ith-layer classification through the iterative way to obtain multiple (i+1)th-layer classifications, recognizing the first-layer classification to which a target face image belongs, continuing recognizing the (j+1)th-layer classification to which the target face image belongs in the jth-layer classification to which the target face image belongs through the iterative way, and recognizing a face image similar to the target face image from the jth-layer classification to which the target face image belongs through the iterative way till no (j+1)th-layer classification exists in the jth-layer classification to which the target face image belongs. Compared with an existing technical scheme, the calculation amount is quite small and face recognition efficiency is greatly improved.

The invention provides a driver face recognition method, system and device and a medium. The method comprises: acquiring a face image of a driver; extracting a face recognition area from the face image, and adjusting the face recognition area to meet a preset recognition condition; inputting the face recognition area into a trained face feature extraction model constructed based on deep learning to obtain a face feature vector; calculating similarity according to a face feature vector output by the face feature extraction model and a face feature vector of a pre-stored image; and if the similarity is greater than a specified threshold, judging that the face is the face of the same person, and if the similarity of a plurality of pre-stored face images is greater than the threshold, judgingthat the pre-stored face image with the maximum similarity and the face image of the driver are the face images of the same person, thereby determining the identity of the driver. The method has the advantages of being high in speed, high in recognition accuracy and good in algorithm robustness, and therefore the requirement for vehicle-mounted face recognition is met.

The invention discloses a face recognition method, device and system and a model training method and device, and belongs to the technical field of face recognition. The method comprises the steps of inputting a to-be-identified face image to a deep learning model; receiving face feature data output by the deep learning model; in the deep learning model, the input layer is used for carrying out data processing on a to-be-identified face image after receiving the to-be-identified face image so as to obtain high-dimensional feature data; the first output layer is used for performing data dimension reduction processing on the high-dimensional feature data to obtain low-dimensional feature data; the feature combination layer is used for preprocessing the low-dimensional feature data and carrying out merging processing on the low-dimensional feature data to obtain combined feature data; and the second output layer is used for carrying out feature fusion on the combined feature data to obtainface feature data. The problems that in the prior art, the face recognition efficiency is low, resource and time consumption is large when a deep learning model is trained, and the training flexibility is low are solved.

The invention provides a face recognition method and device, and the method comprises the steps: inputting a to-be-recognized face depth image into a face recognition model, and obtaining a face recognition result; wherein the face recognition model is obtained by training by taking a face depth sample graph as a sample, the face depth sample graph is an image which is evaluated to be qualified onthe basis of a face thermodynamic weight graph, and the face thermodynamic weight graph can represent the relevance between a region corresponding to the face depth sample graph and a recognition rate in face recognition; the evaluation result can accurately reflect the influence degree of the to-be-evaluated face depth sample image on the recognition rate, and the high-quality face depth sampleimage can be accurately screened out to serve as the input of the face recognition model, so as to reduce the time cost and labor cost of collecting a large number of face depth sample images to testthe recognition rate, and improve the face recognition efficiency.

The invention is applicable to the technical field of image processing, and provides a target face image extraction method and device and terminal equipment, and the target face image extraction method comprises the steps: obtaining a video image comprising a plurality of faces, wherein the video image comprises a plurality of frames of images; performing face detection on the multiple frames of images, and determining a target area corresponding to a target face in each frame of image; wherein the target human face is one or more human faces in the plurality of human faces; determining a motion track corresponding to the target face based on the target area of the target face in each frame of image; wherein the target area in each frame of image corresponds to one face picture; and basedon the posture of the target face in each frame of image, determining at least one target face image in a plurality of face images corresponding to the motion trail. According to the method and the device, the face picture with high quality and low repetition rate can be captured for face recognition, so that the face recognition efficiency can be improved.

The invention discloses a human face recognition method. The method comprises the steps of extracting the features of key points in an acquired face image of a to-be-recognized user, and forming a feature vector by the features of key points; subjecting the feature vector and a training matrix to operation to generate a model, wherein the training matrix is composed of a covariance matrix formed through inputting the feature vector obtained through extracting the features of key points in the acquired face image of the user into a combined Bayesian model and then training the feature vector; comparing the model with human face images in a sample library, and then recognizing the user. According to the technical scheme of the human face recognition method, the features of key points in the acquired face image of the user are extracted to form the feature vector, and then the feature vector is subjected to model training and recognition through the combined Bayesian model. Compared with the current deep learning-based face recognition algorithm, fewer samples are required for model training, and the calculation amount is reduced. The face recognition efficiency can be improved.

The invention relates to a human face identification method and device, a storage medium and an electronic device. The human face identification method comprises steps of receiving human face identification order, detecting a moving state of a device according to a performance mode, switching the device to a second performance mode when the state of the device is static, performing human face identification on a scanned frame image under the second performance mode, switching the device back to the first performance mode when an identification result is obtained, wherein the device has a lowerresource occupancy rate under the first performance mode than being under the second performance mode during the process of human face identification. The human face identification method and device,the storage medium and the electronic device can maintain a balance between improvement in human face identification efficiency and a resource occupancy rate.

The invention provides a face recognition method and system combining 3D structured light, infrared light and visible light. A 3D structured light depth living body algorithm is adopted; by processingthe object depth information acquired by the 3D sensor, combining the visible light and the near-infrared sensor, and through a depth living body and visible light near-infrared algorithm, the safetyof face recognition is improved, the system overhead can be reduced, and the face recognition efficiency and accuracy are improved to the maximum extent.

The invention provides a light supplementing method and device for face recognition and a computer readable storage medium, and the method comprises the steps: obtaining a light sensing value of a current environment when a first face recognition instruction is detected, and judging whether the light sensing value of the current environment is smaller than a preset brightness threshold value or not; If the brightness value is smaller than the preset brightness threshold value, displaying a light supplementing interface, obtaining the initial brightness value of the light supplementing interface, and determining the light supplementing level corresponding to the light sensing value of the current environment according to the corresponding relation between the preset environment light sensing value and the light supplementing level; And determining a primary adjustment parameter value of the light supplementing interface according to the light supplementing level and the initial brightness value, and gradually increasing the light supplementing interface to a level light supplementing brightness threshold value corresponding to the light supplementing level based on the primary adjustment parameter value. Through the mode, the face image acquisition quality and the face recognition efficiency are improved, the user experience is improved, and the technical problem that the facerecognition efficiency is low in an existing dark environment is solved.

The invention discloses a face recognition method, and the method comprises the steps: carrying out the face collection according to a recognition request, and obtaining face information; recognizingthe face information through local face data, and judging whether recognition is passed or not; if the identification is passed, outputting a passing prompt; if the identification is not passed, identifying the face information through cloud face data, and outputting the passing prompt when the identification is passed; according to the face recognition method, the face recognition efficiency canbe improved more effectively, and the user experience is ensured. The invention further discloses a face recognition device, system and equipment and a computer readable storage medium, which all havethe above beneficial effects.

The invention discloses a passenger portrait-based face recognition method. The method comprises the following steps: data acquisition: acquiring passenger travel data of all bus routes in a certain region within a preset time period; constructing a passenger portrait: constructing a multi-dimensional user portrait of each passenger according to the travel data information; face base library construction: according to the travel data information, extracting passenger face images of each bus route, and building a face base library corresponding to each bus route; according to the passenger portraits, extracting frequency information of passengers taking each bus route, setting the passengers with the taking frequency reaching N times as frequent passengers, wherein the face images of the frequent passengers in each bus route serve as the face base library of the bus route; and passenger face recognition: when the passenger takes a bus on site, comparing the passenger with the face in the face base library to complete face recognition.

The invention relates to artificial intelligence, and provides a face recognition method and device based on artificial intelligence, electronic equipment and a medium. The method comprises the stepsof extracting a to-be-recognized image and determining a face area; extracting facial feature information points, constructing a three-dimensional face image of the to-be-recognized image based on theface feature information points; extracting a plurality of target features from the three-dimensional face image, calculating the similarity between the plurality of target features and configurationfeatures in a configuration library, according to the face recognition method and device, multiple face images at multiple angles do not need to be obtained through camera equipment, the target usercan be determined only through one face image, equipment resources are saved, meanwhile, the face recognition efficiency is improved, and the face recognition precision can also be improved. In addition, the invention also relates to a blockchain technology, and the three-dimensional face image is stored in a blockchain.

The embodiment of the invention relates to the technical field of safety early warning, and discloses an early warning method, a server and an early warning system. The early warning method comprisesthe following steps: acquiring a plurality of monitoring videos sent by a plurality of monitoring devices in different time periods; respectively analyzing the plurality of monitoring videos to obtainidentity information and body state information of the user in each monitoring video, and associating the identity information with the body state information; determining a body change trend of theuser according to the plurality of pieces of body state information associated with the identity information of the user; and if the body change trend satisfies a preset condition, triggering an alarm. The invention further provides a server and an early warning system. According to the early warning method, the server and the early warning system provided by the invention, the safety of the usercan be improved.

The embodiment of the invention provides an identity authentication method which comprises the following steps: receiving registration request information of a user, and transmitting the registrationrequest information to a server; receiving response information returned by the server based on the registration request information; starting an image acquisition device to acquire a current face image according to the face data acquisition information, and acquiring current face data of the user through the current face image; uploading the current face data to a server, and obtaining user information of the user; receiving user information of the user provided by the server, and displaying the user information on a display screen; and receiving a confirmation instruction of the user, and transmitting the confirmation instruction to the server to complete user registration. The embodiment of the invention provides an identity authentication system, computer equipment and a readable storage medium. According to the embodiment of the invention, the face recognition efficiency in a complex environment is improved, and the accuracy and safety of information entry are improved.

The invention provides a management control method, device and system of a multi-face recognition engine. The system comprises the components of: a system, a Unified management module, The system comprises at least one face recognition engine and a management control device of the multi-face recognition engine, the management control device of the multi-face recognition engine is in communicationconnection with at least one face recognition engine, and the unified management module is in communication connection with the management control device of the multi-face recognition engine and at least one face recognition engine. The method comprises the following steps of: By calling the interface of each face recognition engine, the identification information and the path information of the face image are transmitted to each face recognition engine, so that each face recognition engine obtains the corresponding face image from the unified storage module according to the received identification information and path information and performs data modeling and analysis according to the respective face recognition algorithm. The application environment and the storage environment of each face recognition engine are unified, the platform construction cost is reduced, and the face recognition efficiency is effectively improved.

The invention relates to a face recognition access control processing method, a gate, a control terminal, a system, a computer device, and a storage medium. The method comprises the steps of: a firstgate detects a human face and calculates a feature value of the human face, sends the feature value of the human face to a second gate, while the first gate compares the feature value of the human face with a first sub-human face database stored in the first gate, the second gate compares the feature value of the human face with a second sub-human face database stored in the second gate and feedsback a comparison result to the first gate. The parallel calculation of the two gates improves the calculation efficiency and the utilization rate of the gate CPU, at the same time, the transmission of the feature value of the human face and the result feedback are local communications, and the communication efficiency is high, so that the efficiency of face recognition of the access control gateis improved.

The invention discloses an intelligent access control device with a face recognition function, and the device comprises a device body; a channel cavity allowing people to pass through is formed in thedevice body, a switch cavity with a leftward opening is formed in the upper side of the right wall of the channel cavity in a communicating mode, and a switch rotating rod is rotatably arranged between the upper wall and the lower wall in the switch cavity; and the end face of the outer circle of the switch rotating rod is fixedly connected with an overturning plate. According to the face recognition device, the lifting height and the steering direction of the face recognition device are adjusted to adapt to face shooting recognition of people going in and out, the lifting of the umbrella stand is adjusted while the face recognition efficiency is higher, and the face recognition device adapts to the height of people to pack plastic bags for people going in and out of umbrellas; meanwhile,in the process that people pass through the access control system, the soles of the people are subjected to air blowing drying, the anti-skid effect is achieved; the channel ground is dehumidified and cleaned after the people pass through, the anti-skid effect of people entering and exiting subsequently is achieved, and the access control device is more intelligent and user-friendly.

The invention provides an identity recognition method and device, and the method comprises the steps: receiving to-be-recognized information transmitted by a terminal, the to-be-recognized informationcomprising face information and a terminal identification; if it is judged that the face information exists in a terminal database corresponding to the terminal identifier, obtaining a client identifier corresponding to the face information from the terminal database, wherein the terminal database has a first preset capacity and changes dynamically. The device is used for executing the method. According to the identity recognition method and device provided by the embodiment of the invention, the identity of the client can be quickly recognized, and the face recognition efficiency is improved.

The invention relates to a face recognition photographing system for an intelligent robot, comprising a controller and a background server, wherein the controller is connected with a high-definition smart camera, a wireless network module, a horizontal motor, a vertical motor, a data transmission module and a power supply module; the high-definition smart camera comprises a microprocessor in connection with the controller; the microprocessor is connected with a target positioning module, an image acquisition processing module, a face image detection module, a face image extraction module, a geomagnetic sensor module, a storage unit, a face image comparison module, a USB interface, and a power supply interface, wherein the image acquisition processing module is connected with an image acquisition module; the power supply module is connected with the wireless network module, the horizontal motor, the vertical motor, the data transmission module, and the power supply interface through power lines; and the background server is connected with the controller through a wireless network. The face recognition photographing system for the intelligent robot in the invention has the advantagesof convenience for use, accurate positioning, fast identification, and convenience for data update maintenance.

The invention relates to a detection system for real-time human body, including gear shafts, the gear shaft is fixedly arranged on the wall surface, a first support bar and a second support bar are arranged on the gear shaft, the first support bar, one end of the second support bar is respectively provided with a first detection camera, second detection camera, the first detection camera, an imageacquisition module,a judgment processing module,a rotating module, a face recognition module are included in the second detection camera. The gear shaft can rotate and drive the first detection camera, as the second detect camera rotates at 360 degrees, compared with the prior art, the present invention improves the face recognition efficiency, and collects a face image of a person through the detecting camera rotates at 360 degrees, further improving the quality of acquiring the face image, thereby improving the face recognition accuracy.

The embodiment of the invention provides a face feature extraction method and device and a face recognition model training method and device. The method comprises the steps that a to-be-recognized face picture and face attribute features corresponding to the face picture are acquired; selecting at least one expert sub-model from a plurality of expert sub-models included in a hybrid expert network as a target sub-model according to the face picture and the face attribute characteristics; and performing feature extraction processing on the face picture through the target sub-model to obtain a face feature corresponding to the face picture. According to the embodiment of the invention, the face recognition effect can be improved, the calculation amount can be reduced, and the recognition efficiency is improved.

The invention discloses a video face recognition method based on an aggregation adversarial network, and belongs to the technical field of video face recognition. According to the method, an aggregation adversarial network constructed by an aggregation network, a discrimination network and an identification network is adopted, the aggregation network and the discrimination network form adversariallearning, and a generated image is closer to a static image of a target set in a competitive mode; and the perception loss is calculated in the high-dimensional feature space through the recognitionnetwork, so that the generated image is closer to the static image of the corresponding target set in perception performance, and the performance of the aggregation network is improved. And the discrimination network adopts a softmax multi-dimensional output form, so that not only can the authenticity of the image be judged, but also the identity category of the image can be discriminated, the identity of the generated image is enabled to be closer to a real value, the subsequent identification is enabled to be more accurate, and the identification efficiency is enabled to be higher.

The invention discloses a face recognition method based on a cosine loss function. The face recognition method comprises the following steps: preprocessing face image data needing face recognition training to form a training sample set; constructing a CNN network, inputting the training sample set into the CNN network to carry out face recognition convolutional neural network training, and outputting a first face feature code after the training is completed; inputting the training sample set into a Thomson Problem model for solving, and calculating a second face feature code; performing recent matching calculation on the first face feature code and the second face feature code, correcting CNN model parameters according to a recent matching result, and outputting a face recognition result until the recent matching result meets a set threshold value. In the face recognition process, the coding vector of the face feature is adopted to replace the original FC, so that the training of the neural network is not influenced by the size of the training data set, and the face recognition efficiency is improved.

The invention relates to the technical field of computers, in particular to a face recognition library construction method and a face payment method and system. The face recognition library construction method comprises the following steps: S1, image feature spaces of multiple face images are established; S2, the image feature spaces are divided into multiple face feature subspaces; S3, clustering the feature subspaces of all the faces; S4, clustering center point information and data category information are obtained; S5, clustering a face recognition library. According to the method, the image feature space of a plurality of face images is split into a plurality of face feature subspaces, each face feature subspace is clustered to obtain clustering center point information and data category information of each face feature subspace, and according to the clustering center point information and the data category information of each face feature subspace, the face recognition library is constructed, so the face recognition process is simple and easy to implement, the face recognition efficiency is improved, and the resource consumption is reduced.