首页> 外国专利> CLASS DISCRIMINATING FEATURE VECTOR-BASED TRAINED SUPPORT VECTOR MACHINE AND A FACE MEMBERSHIP AUTHENTICATION METHOD BASED ON THE SAME

CLASS DISCRIMINATING FEATURE VECTOR-BASED TRAINED SUPPORT VECTOR MACHINE AND A FACE MEMBERSHIP AUTHENTICATION METHOD BASED ON THE SAME

机译:基于分类特征向量的训练支持向量机及基于相同特征的人脸识别方法

摘要

PURPOSE: A class discriminating feature vector-based SVM(Support Vector Machine) and a face membership authentication method based on the same are provided to authenticate a face despite the changes in illumination, facial pose, registrant class configuration, and so on by providing an efficient class discriminating feature vector-based SVM.;CONSTITUTION: A registrant face image set of a training set is normalized, and PCA(Principal Component Analysis) mode spatial Gabor vectors are obtained by projecting a face Gabor bunch onto a PCA mode vector partial space. The face Gabor similarity of registrant face images are required by projecting the face Gabor bunch of the face images onto the PAC mode vector partial space. The class discrimination feature vector of the face images are calculated by suing the face Gabor similarities.;COPYRIGHT KIPO 2011
机译:目的:提供一种基于类别区分特征向量的支持向量机(SVM)和基于该向量的脸部成员身份验证方法,尽管光照,脸部姿势,注册人类别配置等发生了变化,但仍可以对脸部进行身份验证。高效:基于特征向量的基于类的区分向量;构成:对训练集的注册人脸图像集进行归一化,并将人脸Gabor束投影到PCA模式向量局部空间上,从而获得PCA(主成分分析)模式空间Gabor向量。 。通过将面部图像的面部Gabor束投影到PAC模式矢量局部空间上,需要注册面部图像的面部Gabor相似度。通过使用人脸Gabor相似度来计算人脸图像的类别识别特征向量。; COPYRIGHT KIPO 2011

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