8 results about "Face verification" patented technology

Embodiments of the present application provide an image processing method, device, storage medium and program product. The method synchronously performs face verification and key point regression by using an end-to-end single model, and optimizes the multi-stage processing flow in the related art into integrated operation. The calculation delay and memory occupation are significantly reduced, the consumption of calculation resources is reduced, and the method can be deployed in a mobile device or an embedded system with limited calculation resources. Since the classification task and the regression task share the same feature representation, the model can improve the accuracy of face verification while keeping a small amount of parameters, and effectively reduce the probability of misjudging a non-face area as a face. This double protection mechanism ensures that the key point detection result is output only on the confirmed face image, thereby improving the reliability of subsequent applications.

The application discloses a face anti-counterfeiting method and device and a storage medium. The face anti-counterfeiting method comprises the following steps: acquiring a to-be-detected image collected by a 2D monocular camera; acquiring a depth factor corresponding to each pixel coordinate point of the to-be-detected image through a preset face depth model; converting the to-be-detected image into a 3D space information image according to the depth factor and preset camera parameters; judging whether the converted 3D space information image is a plane false face; and if the 3D space information image is not a plane false face, judging whether the to-be-detected image is a three-dimensional false face through a preset three-dimensional anti-counterfeiting model. Thus, the face depth model and the three-dimensional anti-counterfeiting model are used to realize two-dimensional and three-dimensional anti-counterfeiting of the image through the 2D monocular camera. The hardware requirement for the camera is reduced without the action cooperation of the verifier, the face verification efficiency is improved, and the face anti-counterfeiting accuracy is improved.

1. Name of the product in this design: Graphical User Interface for Intelligent Countertops for Electronic Devices. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The rear view, left view, right view, top view, and bottom view are omitted. 6. Purpose of the graphical user interface: The product interface of this design is used to display the graphical user interface of the intelligent counter and to enable human-computer interaction. 7. Graphical User Interface: Providing customers with safe and convenient 24 / 7 service, covering over 90% of traditional businesses such as account opening, fund transfer, wealth management, and foreign exchange. The main view displays the main interface. Click the "Password Reset" menu on the main view to enter interface state diagram 1; click the "I have read and agree" button in interface state diagram 1 to enter interface state diagram 2; after inserting your ID card and undergoing system verification, enter interface state diagram 3; after successfully removing your ID card, enter interface state diagram 4; after performing face verification in interface state diagram 4, click the "Confirm and Continue" button to enter interface state diagram 5; after selecting the electronic card medium in interface state diagram 5, enter interface state diagram 6; after selecting a card in interface state diagram 6, click the "Confirm and Continue" button to enter interface state diagram 7; after checking the agreement in interface state diagram 7, enter interface state diagram 8; click the "Confirm and Continue" button in interface state diagram 8 to enter interface state diagram 9; sign in interface state diagram 9 and click the "Confirm and Continue" button to enter interface state diagram 10; after fingerprint verification in interface state diagram 10, click the "Pass" button to enter interface state diagram 11; after setting the password in interface state diagram 11, enter interface state diagram 12, the transaction results page.

The application discloses a kind of campus face feature library management method and system, it is related to campus security technical field, method includes the identity information of each campus personnel and corresponding face image is collected, feature extraction is carried out based on pre-training face verification algorithm, generates corresponding campus personnel face image feature vector set;Real-time verification is carried out when the face image of acquisition is obtained, and real-time face verification data is generated;The feature vector of the face image of the user audit confirmation of the application is grouped according to the feature difference size by verification failure, the feature vector of each group of face image reaches certain frequency when appearing, only then the group feature vector is used to the corresponding face feature library incremental update, prevent abnormal outlier feature pollution user's face feature library, while also can the face image of user more common appearance, such as glasses, mask, hairstyle and makeup, incremental update to corresponding face feature library, so that user next time using same face image verification can be verified.

A face recognition system and method based on a recursive process are provided. The face recognition system may comprise: a local device for generating, as detection data, a detection result obtained by using an object detection model with respect to an image locally collected using a camera; and a face recognition device for receiving the detection data from the local device and performing face recognition, wherein the face recognition device: stores the detection data in a storage medium; reads a plurality of frames included in a predetermined period from the storage medium; extracts a multi-dimensional face vector configured according to an index of the camera, an index of the period, an index of the frame, and an index of an extracted feature, the face vector being cumulatively stored in the storage medium in units of the period; executes a recursive process for performing identifier matching on the face vector for each of the plurality of frames; and performs face verification or face identification on the basis of the identifier for which matching has been performed through the recursive process.

The application discloses a privacy protection face recognition method based on five sense organs physical mask and dynamic confrontation and belongs to the field of computer vision and information security.The method comprises the following steps: five key points of a face are extracted to generate a five sense organs physical mask, residual information is obtained through reversible frequency domain transformation and a generator, and the protected residual error is combined with the mask to be sent into a recognizer to complete face verification; the five sense organs mask shields the non-core privacy area of the face, a pixel-level attacker is introduced to construct an active confrontation defense closed loop, and the technical defects that existing privacy face recognition technology is easy to leak face visual clues, passive protection is easy to be cracked by reconstruction attack, and recognition accuracy and training efficiency are difficult to be considered are solved, the face data anti-reconstruction attack capability is greatly improved under the premise of ensuring the face recognition accuracy, the model training algorithm cost is reduced, and the method can be widely applied to various face verification scenes such as access control, payment and public security.

The embodiment of the invention discloses an image processing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining multi-modal detection information which corresponds to a to-be-detected image and comprises image information, equipment parameter information and behavior track information; inputting each piece of feature information in the multi-modal detection information into a feature extraction network, and determining corresponding feature information; fusing the feature information, and determining fusion features with time sequence consistency; counterfeit features in the fusion features are detected, a detection result is determined, and the detection result is used for representing whether the to-be-detected image is a counterfeit image or not. Therefore, according to the embodiment of the invention, image counterfeiting detection is carried out by using the multi-modal detection information, so that the robustness of counterfeited face detection and the security of face verification can be improved.

A method performed by an edge device (e.g., a dash camera) is disclosed to automatically trigger a security action. The method includes storing a face embedding of a first person that is expected to be inside a vehicle, capturing, using one or more cameras, one or more images of a face of a second person inside the vehicle, generating a face embedding of the second person based on analyzing the one or more images of the face of the second person using a face embedding machine learning model, determining whether the face of the second person matches a face of the first person based on comparing the face embedding of the second person to the face embedding of the first person using a face verification machine learning model, and triggering a security action in response to determining that the faces do not match.