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公开(公告)号：US20160070956A1
公开(公告)日：2016-03-10
申请号：US14841928
申请日：2015-09-01
Applicant: Huawei Technologies Co., Ltd.
Inventor： Chaochao Lu , Chunjing Xu , Xiaoou Tang
IPC: G06K9/00
CPC classification number: G06K9/00288 , G06K9/00268 , G06K9/6232
Abstract: A method and an apparatus for generating a facial feature verification model. The method includes acquiring N input facial images, performing feature extraction on the N input facial images, to obtain an original feature representation of each facial image, and forming a face sample library, for samples of each person with an independent identity, obtaining an intrinsic representation of each group of face samples in at least two groups of face samples, training a training sample set of the intrinsic representation, to obtain a Bayesian model of the intrinsic representation, and obtaining a facial feature verification model according to a preset model mapping relationship and the Bayesian model of the intrinsic representation. In the method and apparatus for generating a facial feature verification model in the embodiments of the present disclosure, complexity is low and a calculation amount is small.
Abstract translation: 一种用于生成面部特征验证模型的方法和装置。 该方法包括获取N个输入的面部图像，对N个输入的面部图像执行特征提取，以获得每个面部图像的原始特征表示，以及形成一个具有独立身份的每个人的样本的面部样本库， 在至少两组面部样本中对每组面部样本的表示，训练内在表示的训练样本集合，以获得内在表示的贝叶斯模型，并且根据预设模型映射关系获得面部特征验证模型 和贝叶斯模型的内在表征。 在本公开的实施例中用于生成面部特征验证模型的方法和装置中，复杂度低，计算量小。
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公开(公告)号：US20170031953A1
公开(公告)日：2017-02-02
申请号：US15278461
申请日：2016-09-28
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xiaoou Tang , Chaochao Lu
CPC classification number: G06F16/5838 , G06K9/00288 , G06K9/6218 , G06K9/6232 , G06K9/629 , G06N7/005 , G06N20/00
Abstract: A method for verifying facial data and a corresponding system, which comprises retrieving a plurality of source-domain datasets from a first database and a target-domain dataset from a second database different from the first database; determining a latent subspace matching with target-domain dataset best and a posterior distribution for the determined latent subspace from the target-domain dataset and the source-domain datasets; determining information shared between the target-domain data and the source-domain datasets; and establishing a Multi-Task learning model from the posterior distribution P and the shared information M on the target-domain dataset and the source-domain datasets.
Abstract translation: 一种用于验证面部数据的方法和相应的系统，其包括从不同于第一数据库的第二数据库从第一数据库和目标域数据集检索多个源域数据集; 确定与目标域数据集最佳匹配的潜在子空间和来自目标域数据集和源域数据集的确定的潜在子空间的后验分布; 确定目标域数据和源域数据集之间共享的信息; 并从目标域数据集和源域数据集上的后验分布P和共享信息M建立多任务学习模型。
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公开(公告)号：US10339177B2
公开(公告)日：2019-07-02
申请号：US15278461
申请日：2016-09-28
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xiaoou Tang , Chaochao Lu
Abstract: A method for verifying facial data and a corresponding system, which comprises retrieving a plurality of source-domain datasets from a first database and a target-domain dataset from a second database different from the first database; determining a latent subspace matching with target-domain dataset best and a posterior distribution for the determined latent subspace from the target-domain dataset and the source-domain datasets; determining information shared between the target-domain data and the source-domain datasets; and establishing a Multi-Task learning model from the posterior distribution P and the shared information M on the target-domain dataset and the source-domain datasets.
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公开(公告)号：US09514356B2
公开(公告)日：2016-12-06
申请号：US14841928
申请日：2015-09-01
Applicant: Huawei Technologies Co., Ltd.
Inventor： Chaochao Lu , Chunjing Xu , Xiaoou Tang
CPC classification number: G06K9/00288 , G06K9/00268 , G06K9/6232
Abstract: A method and an apparatus for generating a facial feature verification model. The method includes acquiring N input facial images, performing feature extraction on the N input facial images, to obtain an original feature representation of each facial image, and forming a face sample library, for samples of each person with an independent identity, obtaining an intrinsic representation of each group of face samples in at least two groups of face samples, training a training sample set of the intrinsic representation, to obtain a Bayesian model of the intrinsic representation, and obtaining a facial feature verification model according to a preset model mapping relationship and the Bayesian model of the intrinsic representation. In the method and apparatus for generating a facial feature verification model in the embodiments of the present disclosure, complexity is low and a calculation amount is small.
Abstract translation: 一种用于生成面部特征验证模型的方法和装置。 该方法包括获取N个输入的面部图像，对N个输入的面部图像执行特征提取，以获得每个面部图像的原始特征表示，以及形成一个具有独立身份的每个人的样本的面部样本库， 在至少两组面部样本中对每组面部样本的表示，训练内在表示的训练样本集合，以获得内在表示的贝叶斯模型，并且根据预设模型映射关系获得面部特征验证模型 和贝叶斯模型的内在表征。 在本公开的实施例中用于生成面部特征验证模型的方法和装置中，复杂度低，计算量小。
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