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HUMAN EYE MODEL TRAINING METHOD, HUMAN EYE RECOGNITION METHOD, APPARATUS, DEVICE AND MEDIUM

机译:人眼模型训练方法,人眼识别方法,装置,设备和介质

摘要

A human eye model training method, a human eye recognition method, an apparatus, a device and a medium. The human eye model training method comprises: acquiring a face image sample and marking the face image sample so as to obtain face image sample data, and extracting a feature vector of the face image sample, wherein the face image sample data comprises the face image sample and marking data (S10); dividing the face image sample data into training sample data and verification sample data (S20); using the training sample data to train a support vector machine classifier so as to obtain a critical plane of the support vector machine classifier (S30); calculating a vector distance of a feature vector of a verification sample in the verification sample data and the critical plane (S40); acquiring a preset true positive rate or a preset false positive rate, and acquiring a classification threshold according to the vector distance and the marking data corresponding to the verification sample (S50); acquiring a human eye determination model according to the classification threshold (S60). The described method may obtain a human eye determination model that is highly accurate in determining whether a human eye is occluded.
机译:人眼模型训练方法,人眼识别方法,设备,装置和介质。该人眼模型训练方法包括:获取人脸图像样本并标记该人脸图像样本以获得人脸图像样本数据,并提取该人脸图像样本的特征向量,其中人脸图像样本数据包括人脸图像样本。和标记数据(S10);将面部图像样本数据分为训练样本数据和验证样本数据(S20);使用训练样本数据训练支持向量机分类器,以获得支持向量机分类器的临界面(S30);计算验证样本数据中的验证样本特征向量与临界平面的向量距离(S40);获取预设的真阳性率或预设的假阳性率,并根据所述矢量距离和所述验证样本对应的标记数据获取分类阈值(S50);根据分类阈值获取人眼判断模型(S60)。所描述的方法可以获得在确定人眼是否被遮挡中高度准确的人眼确定模型。

著录项

  • 公开/公告号WO2019232866A1

    专利类型

  • 公开/公告日2019-12-12

    原文格式PDF

  • 申请/专利权人 PING AN TECHNOLOGY (SHENZHEN) CO. LTD.;

    申请/专利号WO2018CN94341

  • 发明设计人 DAI LEI;

    申请日2018-07-03

  • 分类号G06K9;

  • 国家 WO

  • 入库时间 2022-08-21 11:14:24

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