-
11.
公开(公告)号:US10769256B2
公开(公告)日:2020-09-08
申请号:US15469984
申请日:2017-03-27
Applicant: Samsung Electronics Co., Ltd.
Inventor: Jaejoon Han , Jungbae Kim , Seon Min Rhee , Seungju Han , Minsu Ko
IPC: G06F21/00 , G06F21/32 , G06F16/23 , G06F16/51 , G06K9/00 , G06K9/62 , G07C9/37 , G06F21/45 , G06F21/36 , G06K9/46 , H04L29/06
Abstract: An adaptive updating method of an enrollment database is disclosed. The method may include extracting a first feature vector from an input image of a user, determining whether the input image is to be enrolled in an enrollment database based on the first feature vector, second feature vectors of enrollment images including initial enrollment images enrolled in the enrollment database, and a representative vector representing the initial enrollment images, and enrolling the input image in the enrollment database based on a result of the determining.
-
公开(公告)号:US12272173B2
公开(公告)日:2025-04-08
申请号:US18515798
申请日:2023-11-21
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Youngjun Kwak , Minsu Ko , Youngsung Kim , Heewon Kim , Ju Hwan Song , Byung In Yoo , Seon Min Rhee , Yong-il Lee , Jiho Choi , Seungju Han
Abstract: A processor-implemented method includes generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image.
-
公开(公告)号:US12260523B2
公开(公告)日:2025-03-25
申请号:US17318287
申请日:2021-05-12
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Insoo Kim , Seungju Han , Seong-jin Park , Jiwon Baek , Jaejoon Han
IPC: G06T5/70 , G06N3/045 , G06N3/08 , G06T3/4046 , G06T5/73
Abstract: An image recognition method includes: receiving an input image of a first quality; extracting an input feature of a second quality of the input image from the input image by inputting the input image to an encoding model in an image recognizing model; and generating a recognition result for the input image based on the input feature.
-
公开(公告)号:US12062251B2
公开(公告)日:2024-08-13
申请号:US18312997
申请日:2023-05-05
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: SungUn Park , Jihye Kim , Jaejoon Han , Minsu Ko , Seungju Han , Jinwoo Son , Changyong Son
IPC: G06F21/00 , G06F16/583 , G06F18/22 , G06F21/32 , G06T7/73 , G06V40/16 , G06V40/40 , H04N23/90 , G06V10/75
CPC classification number: G06V40/172 , G06F16/5838 , G06F18/22 , G06F21/32 , G06T7/74 , G06V40/45 , H04N23/90 , G06T2207/10024 , G06T2207/10048 , G06T2207/20024 , G06T2207/20081 , G06T2207/20084 , G06V10/759 , G06V40/165 , G06V40/171
Abstract: An image matching method includes extracting, from a first image of an object, a landmark patch including a landmark point of the object, extracting, from a second image of the object, a target patch corresponding to the landmark patch; and determining a target point in the second image corresponding to the landmark point based on a matching between the landmark patch and the target patch.
-
公开(公告)号:US11810397B2
公开(公告)日:2023-11-07
申请号:US17208048
申请日:2021-03-22
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Jiwon Baek , Seong-Jin Park , Seungju Han , Insoo Kim , Jaejoon Han
IPC: G06V40/16 , G06T7/73 , G06V10/75 , G06N3/04 , G06N3/08 , G06T3/40 , G06T3/60 , G06T9/00 , G06F18/214
CPC classification number: G06V40/172 , G06F18/214 , G06N3/04 , G06N3/08 , G06T3/40 , G06T3/60 , G06T7/73 , G06T9/002 , G06V10/751 , G06V40/171 , G06T2207/20081 , G06T2207/20084 , G06T2207/30201
Abstract: A processor-implemented facial image generating method includes: determining a first feature vector associated with a pose and a second feature vector associated with an identity by encoding an input image including a face; determining a flipped first feature vector by flipping the first feature vector with respect to an axis in a corresponding space; determining an assistant feature vector based on the flipped first feature vector and rotation information corresponding to the input image; determining a final feature vector based on the first feature vector and the assistant feature vector; and generating an output image including a rotated face by decoding the final feature vector and the second feature vector based on the rotation information.
-
公开(公告)号:US11790065B2
公开(公告)日:2023-10-17
申请号:US17240059
申请日:2021-04-26
Applicant: Samsung Electronics Co., Ltd.
Inventor: Sungjoo Suh , Seungju Han , Jae-Joon Han , Chang Kyu Choi
CPC classification number: G06F21/32 , H04L63/0861 , H04L63/105 , H04L2463/082
Abstract: A user verification apparatus may perform user verification using multiple biometric verifiers. The user verification apparatus may set a termination stage of one or more biometric verifiers. Multiple biometric verifiers may be used to generate outputs, for which separate termination stages are set to establish a particular combination of set termination stages associated with the multiple biometric verifiers, and the user verification apparatus may fuse outputs of the biometric verifiers based on the particular combination of set termination stages. The user verification apparatus may verify a user based on a result of the fusing, and an unlocking command signal may be generated based on the verifying. The unlocking command signal may be generated to selectively grant access, to the verified user, to one or more elements of a device. The device may be a vehicle.
-
公开(公告)号:US11636577B2
公开(公告)日:2023-04-25
申请号:US16867749
申请日:2020-05-06
Applicant: Samsung Electronics Co., Ltd.
Inventor: Seong-Jin Park , Jiwon Baek , Seungju Han , Minsu Ko , Solae Lee , Hana Lee
Abstract: A processor-implemented method with blur estimation includes: acquiring size information of an input image; resizing the input image to generate a target image of a preset size; estimating a blur of the target image; and estimating a blur of the input image based on the size information of the input image.
-
公开(公告)号:US11532177B2
公开(公告)日:2022-12-20
申请号:US15864232
申请日:2018-01-08
Applicant: Samsung Electronics Co., Ltd.
Inventor: Changyong Son , Deoksang Kim , Minsu Ko , Jinwoo Son , Seungju Han , Chang Kyu Choi , Jae-Joon Han
Abstract: A face verification method and apparatus is disclosed. The face verification method includes selecting a current verification mode, from among plural verification modes, to be implemented for the verifying of the face, determining one or more recognizers, from among plural recognizers, based on the selected current verification mode, extracting feature information from information of the face using at least one of the determined one or more recognizers, and indicating whether a verification is successful based on the extracted feature information.
-
公开(公告)号:US20220397391A1
公开(公告)日:2022-12-15
申请号:US17887924
申请日:2022-08-15
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor: Suyeon LEE , Unjeong KIM , Hyuck CHOO , Seungju Han , Hyochul KIM
Abstract: An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.
-
公开(公告)号:US11341365B2
公开(公告)日:2022-05-24
申请号:US16913205
申请日:2020-06-26
Applicant: Samsung Electronics Co., Ltd.
Inventor: Seong-Jin Park , Insoo Kim , Seungju Han , Jiwon Baek , Ju Hwan Song , Jaejoon Han
Abstract: A processor-implemented neural network method includes: determining, using a neural network, a feature vector based on a training image of a first class among a plurality of classes; determining, using the neural network, plural feature angles between the feature vector and class vectors of other classes among the plurality of classes; determining a margin based on a class angle between a first class vector of the first class and a second class vector of a second class, among the class vectors, and a feature angle between the feature vector and the first class vector; determining a loss value using a loss function including an angle with the margin applied to the feature angle and the plural feature angles; and training the neural network by updating, based on the loss value, either one or both of one or more parameters of the neural network and one or more of the class vectors.
-
-
-
-
-
-
-
-
-