ANTI-SPOOFING METHOD AND APPARATUS

    公开(公告)号:US20220318354A1

    公开(公告)日:2022-10-06

    申请号:US17668618

    申请日:2022-02-10

    摘要: An anti-spoofing method includes detecting first information related to whether the biometric information is forged, based on a first output vector of a first neural network configured to detect whether the biometric information is forged from the input data, extracting an input embedding vector including a feature of biometric information of a user from input data including the biometric information, calculating a similarity value of the input embedding vector based on a fake embedding vector and either one or both of a real embedding vector and an enrollment embedding vector that are provided in advance, calculating a total forgery score based on the similarity value and a second output vector of the first neural network according to whether the first information is detected, and detecting second information related to whether the biometric information is forged, based on the total forgery score.

    METHOD AND APPARATUS THAT DETECTS SPOOFING OF BIOMETRIC INFORMATION

    公开(公告)号:US20220188556A1

    公开(公告)日:2022-06-16

    申请号:US17340389

    申请日:2021-06-07

    IPC分类号: G06K9/00 G06F21/32

    摘要: A method and apparatus that detects whether biometric information is spoofed is provided. The method receives, from a sensor, first feature information including a static feature associated with biometric information of a user, and a dynamic feature obtained based on images related to the biometric information, detects whether the biometric information is spoofed based on a first score calculated based on the first feature information, fuses the first score with a second score calculated based on second feature information extracted from the images, based on a result of the detecting that the biometric information is spoofed based on the first score, and detects that the biometric information is spoofed based on a fused score.

    METHOD AND APPARATUS WITH AUTHENTICATION AND NEURAL NETWORK TRAINING

    公开(公告)号:US20210166071A1

    公开(公告)日:2021-06-03

    申请号:US16913205

    申请日:2020-06-26

    IPC分类号: G06K9/62 G06N3/04 G06N3/08

    摘要: A processor-implemented neural network method includes: determining, using a neural network, a feature vector based on a training image of a first class among a plurality of classes; determining, using the neural network, plural feature angles between the feature vector and class vectors of other classes among the plurality of classes; determining a margin based on a class angle between a first class vector of the first class and a second class vector of a second class, among the class vectors, and a feature angle between the feature vector and the first class vector; determining a loss value using a loss function including an angle with the margin applied to the feature angle and the plural feature angles; and training the neural network by updating, based on the loss value, either one or both of one or more parameters of the neural network and one or more of the class vectors.

    FACE VERIFICATION METHOD AND APPARATUS

    公开(公告)号:US20210089754A1

    公开(公告)日:2021-03-25

    申请号:US17111907

    申请日:2020-12-04

    IPC分类号: G06K9/00 G06K9/78 G06K9/62

    摘要: Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.