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公开(公告)号：US20200005146A1
公开(公告)日：2020-01-02
申请号：US16564494
申请日：2019-09-09
Applicant: Samsung Electronics Co., Ltd.
Inventor： Changyong SON , Jinwoo SON , Byungin YOO , Chang Kyu CHOI , Jae-Joon HAN
Abstract: A lightened neural network, method, and apparatus, and recognition method and apparatus implementing the same. A neural network includes a plurality of layers each comprising neurons and plural synapses connecting neurons included in neighboring layers. Synaptic weights with values greater than zero and less than a preset value of a variable a, which is greater than zero, may be at least partially set to zero. Synaptic weights with values greater than a preset value of a variable b, which is greater than zero, may be at least partially set to the preset value of the variable b.
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公开(公告)号：US20190034708A1
公开(公告)日：2019-01-31
申请号：US16148587
申请日：2018-10-01
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Byungin YOO , Youngjun KWAK , Jungbae KIM , Jinwoo SON , Changkyo LEE , Chang Kyu CHOI , Jaejoon HAN
CPC classification number: G06K9/00288 , G06K9/00107 , G06K9/00114 , G06K9/00228 , G06K9/00268 , G06K9/00899 , G06K9/00906 , G06K9/50 , G06N3/04 , G06N3/08
Abstract: A liveness test method and apparatus is disclosed. A processor implemented liveness test method includes extracting an interest region of an object from a portion of the object in an input image, performing a liveness test on the object using a neural network model-based liveness test model, the liveness test model using image information of the interest region as provided first input image information to the liveness test model and determining liveness based at least on extracted texture information from the information of the interest region by the liveness test model, and indicating a result of the liveness test.
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公开(公告)号：US20180285628A1
公开(公告)日：2018-10-04
申请号：US15833292
申请日：2017-12-06
Applicant: Samsung Electronics Co., Ltd.
Inventor： Changyong SON , Wonsuk CHANG , Deoksang KIM , Dae-Kyu SHIN , Byungin YOO , Seungju HAN , Jaejoon HAN , Jinwoo SON , Chang Kyu CHOI
CPC classification number: G06K9/00281 , G06K9/00228 , G06K9/00261 , G06K9/00288 , G06K9/00302 , G06K9/00906 , G06K9/6215 , G06K9/78
Abstract: 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.
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公开(公告)号：US20180032867A1
公开(公告)日：2018-02-01
申请号：US15655203
申请日：2017-07-20
Applicant: Samsung Electronics Co., Ltd.
Inventor： Changyong SON , Jinwoo SON , Byungin YOO , Chang Kyu CHOI , Jae-Joon HAN
Abstract: A lightened neural network, method, and apparatus, and recognition method and apparatus implementing the same. A neural network includes a plurality of layers each comprising neurons and plural synapses connecting neurons included in neighboring layers. Synaptic weights with values greater than zero and less than a preset value of a variable a, which is greater than zero, may be at least partially set to zero. Synaptic weights with values greater than a preset value of a variable b, which is greater than zero, may be at least partially set to the preset value of the variable b.
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公开(公告)号：US20170046563A1
公开(公告)日：2017-02-16
申请号：US15189454
申请日：2016-06-22
Applicant: Samsung Electronics Co., Ltd.
Inventor： Jungbae KIM , Ruslan SALAKHUTDINOV , Jaejoon HAN , Byungin YOO
CPC classification number: G06K9/00275 , G06K9/00241 , G06K9/00288 , G06K9/4628 , G06K9/4661 , G06K9/6262 , G06K9/6272
Abstract: A training method of training an illumination compensation model includes extracting, from a training image, an albedo image of a face area, a surface normal image of the face area, and an illumination feature, the extracting being based on an illumination compensation model; generating an illumination restoration image based on the albedo image, the surface normal image, and the illumination feature; and training the illumination compensation model based on the training image and the illumination restoration image.
Abstract translation: 训练照明补偿模式的训练方法包括从训练图像中提取面部区域的反照率图像，面部区域的表面法线图像和照明特征，所述提取基于照明补偿模型; 基于反照率图像，表面法线图像和照明特征生成照明恢复图像; 并基于训练图像和照明恢复图像训练照明补偿模型。
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Patent Agency Ranking
公开(公告)号：US20160379041A1
公开(公告)日：2016-12-29
申请号：US15188437
申请日：2016-06-21
Applicant: Samsung Electronics Co., Ltd.
Inventor： Seon Min RHEE , Jungbae KIM , Byungin YOO , Jaejoon HAN , Seungju HAN
CPC classification number: G06K9/00275 , G06K9/00208 , G06K9/00248 , G06K9/00288 , G06K9/6271 , G06K9/6296 , G06T15/04 , G06T19/20 , G06T2219/2021
Abstract: Face recognition of a face, to determine whether the face correlates with an enrolled face, may include generating a personalized three-dimensional (3D) face model based on a two-dimensional (2D) input image of the face, acquiring 3D shape information and a normalized 2D input image of the face based on the personalized 3D face model, generating feature information based on the 3D shape information and pixel color values of the normalized 2D input image, and comparing the feature information with feature information associated with the enrolled face. The feature information may include first and second feature information generated based on applying first and second deep neural network models to the pixel color values of the normalized 2D input image and the 3D shape information, respectively. The personalized 3D face model may be generated based on transforming a generic 3D face model based on landmarks detected in the 2D input image.
Abstract translation: 面部识别，以确定面部与登记面部相关是否可以包括基于面部的二维（2D）输入图像生成个性化三维（3D）面部模型，获取3D形状信息和 基于个性化3D脸部模型的面部的归一化2D输入图像，基于3D形状信息和归一化2D输入图像的像素颜色值生成特征信息，以及将特征信息与与注册面相关联的特征信息进行比较。 特征信息可以包括基于将第一和第二深层神经网络模型应用于归一化2D输入图像和3D形状信息的像素颜色值而生成的第一和第二特征信息。 可以基于基于在2D输入图像中检测到的地标来变换通用3D脸部模型来生成个性化3D脸部模型。
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公开(公告)号：US20220172510A1
公开(公告)日：2022-06-02
申请号：US17677275
申请日：2022-02-22
Applicant: Samsung Electronics Co., Ltd.
Inventor： Changyong SON , Wonsuk CHANG , Deoksang KIM , Dae-Kyu SHIN , Byungin YOO , Seungju HAN , Jaejoon HAN , Jinwoo SON , Chang Kyu CHOI
Abstract: 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.
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18.发明申请公开(公告)号：US20210073582A1
公开(公告)日：2021-03-11
申请号：US17101552
申请日：2020-11-23
Applicant: Samsung Electronics Co., Ltd.
Inventor： Byungin YOO , Youngjun KWAK , Jungbae KIM , Seon Min RHEE , Seungju HAN , Jaejoon HAN , Wonjun HWANG
Abstract: A method and an apparatus for recognizing an object are disclosed. The apparatus may extract a plurality of features from an input image using a single recognition model and recognize an object in the input image based on the extracted features. The single recognition model may include at least one compression layer configured to compress input information and at least one decompression layer configured to decompress the compressed information to determine the features.
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公开(公告)号：US20180373924A1
公开(公告)日：2018-12-27
申请号：US15896253
申请日：2018-02-14
Applicant: Samsung Electronics Co., Ltd.
Inventor： Byungin YOO , Youngjun KWAK , Youngsung KIM , JaeJoon HAN
CPC classification number: G06K9/00288 , G06F21/32 , G06K9/00248 , G06K9/00281 , G06K9/4628 , G06K9/6262
Abstract: Disclosed is a facial verification apparatus and method. The facial verification apparatus is configured to detect a face area of a user from an obtained input image, generate a plurality of image patches, differently including respective portions of the detected face area, based on a consideration of an image patch set determination criterion with respect to the detected face area, extract a feature value corresponding to a face of the user based on an image patch set including the generated plurality of image patches, determine whether a facial verification is successful based on the extracted feature value, and indicate a result of the determination of whether the facial verification is successful.
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公开(公告)号：US20180276488A1
公开(公告)日：2018-09-27
申请号：US15886875
申请日：2018-02-02
Applicant: Samsung Electronics Co., Ltd.
Inventor： Byungin YOO , Jingtao XU , Chao ZHANG , Hao FENG , Yanhu SHAN , Youngjun KWAK , Youngsung KIM , Wonsuk CHANG , Jaejoon HAN
IPC: G06K9/00
CPC classification number: G06K9/00906 , G06K9/00228 , G06K9/00275 , G06K9/00288
Abstract: A liveness test method and apparatus is disclosed. The liveness test method includes detecting a face region in an input image for a test target, implementing a first liveness test to determine a first liveness value based on a first image corresponding to the detected face region, implementing a second liveness test to determine a second liveness value based on a second image corresponding to a partial face region of the detected face region, implementing a third liveness test to determine a third liveness value based on an entirety of the input image or a full region of the input image that includes the detected face region and a region beyond the detected face region, and determining a result of the liveness test based on the first liveness value, the second liveness value, and the third liveness value.
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