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公开(公告)号：US10002296B2
公开(公告)日：2018-06-19
申请号：US15167388
申请日：2016-05-27
Applicant: Huawei Technologies Co., Ltd.
Inventor： Limin Wang , Yu Qiao , Wei Li , Chunjing Xu , Xiaoou Tang
CPC classification number: G06K9/00718 , G06F16/70 , G06F16/783 , G06F16/786 , G06K9/00724 , G06K9/00744 , G06K9/00758 , G06K9/00765 , G06K9/6218
Abstract: A video classification method and apparatus relate to the field of electronic and information technologies, so that precision of video classification can be improved. The method includes: segmenting a video in a sample video library according to a time sequence, to obtain a segmentation result, and generating a motion atom set; generating, by using the motion atom set and the segmentation result, a motion phrase set that can indicate a complex motion pattern, and generating a descriptive vector, based on the motion phrase set, of the video in the sample video library; and determining, by using the descriptive vector, a to-be-detected video whose category is the same as that of the video in the sample video library. The method is applicable to a scenario of video classification.
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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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Patent Agency Ranking
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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公开(公告)号：US10521469B2
公开(公告)日：2019-12-31
申请号：US15094675
申请日：2016-04-08
Applicant: Huawei Technologies Co., Ltd.
Inventor： Shi Qiu , Xiaogang Wang , Wenqi Ju , Jianzhuang Liu , Xiaoou Tang
IPC: G06F16/583 , G06F16/28 , G06N20/00 , G06F16/901 , G06F16/2457
Abstract: The present disclosure relates to an image re-ranking method, which includes: performing image searching by using an initial keyword, obtaining, by calculation, an anchor concept set of a search result according to the search result corresponding to the initial keyword, obtaining, by calculation, a weight of a correlation between anchor concepts in the anchor concept set, and forming an anchor concept graph ACG by using the anchor concepts in the anchor concept set as vertexes and the weight of the correlation between anchor concepts as a weight of a side between the vertexes; acquiring a positive training sample by using the anchor concepts, and training a classifier by using the positive training sample; obtaining a concept projection vector by using the ACG and the classifier; calculating an ACG distance between images in the search result corresponding to the initial keyword; and ranking the images according to the ACG distance.
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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：US20160275355A1
公开(公告)日：2016-09-22
申请号：US15167388
申请日：2016-05-27
Applicant: Huawei Technologies Co., Ltd.
Inventor： Limin Wang , Yu Qiao , Wei Li , Chunjing Xu , Xiaoou Tang
CPC classification number: G06K9/00718 , G06F17/30781 , G06F17/30784 , G06F17/30811 , G06K9/00724 , G06K9/00744 , G06K9/00758 , G06K9/00765 , G06K9/6218
Abstract: A video classification method and apparatus relate to the field of electronic and information technologies, so that precision of video classification can be improved. The method includes: segmenting a video in a sample video library according to a time sequence, to obtain a segmentation result, and generating a motion atom set; generating, by using the motion atom set and the segmentation result, a motion phrase set that can indicate a complex motion pattern, and generating a descriptive vector, based on the motion phrase set, of the video in the sample video library; and determining, by using the descriptive vector, a to-be-detected video whose category is the same as that of the video in the sample video library. The method is applicable to a scenario of video classification.
Abstract translation: 视频分类方法和装置涉及电子和信息技术领域，从而可以提高视频分类的精度。 该方法包括：根据时间序列对样本视频库中的视频进行分割，以获得分割结果，并生成运动原子集; 通过使用运动原子集合和分割结果，生成可以指示复杂运动模式的运动短语集合，并且基于运动短语集合生成示例视频库中的视频的描述向量; 以及通过使用描述向量来确定其类别与样本视频库中的视频的类别相同的待检测视频。 该方法适用于视频分类场景。
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