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公开(公告)号：US11688198B1
公开(公告)日：2023-06-27
申请号：US17457551
申请日：2021-12-03
发明人： Rajeev Ranjan , Gerard Guy Medioni , Manoj Aggarwal , Dilip Kumar
IPC分类号： G06V40/13 , G06V10/94 , G06F18/213 , G06F18/214
CPC分类号： G06V40/1318 , G06F18/213 , G06F18/2148 , G06V10/95
摘要： A biometric identification system uses inputs acquired using different modalities. A model having an intersection branch and an XOR branch is trained to determine an embedding using features present in all modalities (an intersection of modalities), and features that are distinctive to each modality (an XOR of that modality relative to the other modality(s)). During training, a first loss function is used to determine a first loss value with respect to the branches. Probability distributions are determined for the output from the branches, corresponding to the intersection and XORs of each modality. A second loss function uses these probability distributions to determine a second loss value. A total loss function for training the model may be a sum of the first loss and the second loss. Once trained, the model may process query inputs to determine embedding data for comparison with embedding data of a previously enrolled user.
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公开(公告)号：US11663805B1
公开(公告)日：2023-05-30
申请号：US17209845
申请日：2021-03-23
CPC分类号： G06V10/25 , G06K9/6215 , G06K9/6262 , G06V40/1335 , G06V40/1347 , G06V40/1365
摘要： This disclosure describes a user-recognition system that may perform one or more verification methods upon identifying a previous image that matches a current image of a palm of a user. For instance, the user-recognition system may perform the verification method(s) as part of the recognition method (e.g., after recognizing a matching image), in response to an audit process, in response to a request to re-analyze the image data (e.g., because a user indicates that he or she was not associated with a particular purchase or shopping session), and/or the like.
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公开(公告)号：US20190392189A1
公开(公告)日：2019-12-26
申请号：US16014843
申请日：2018-06-21
发明人： Dilip Kumar , Manoj Aggarwal , George Leifman , Gerard Guy Medioni , Nikolai Orlov , Natan Peterfreund , Korwin Jon Smith , Dmitri Veikherman , Sora Kim
摘要： A non-contact biometric identification system includes a hand scanner that generates images of a user's palm. Images are acquired using light of a first polarization at a first time show surface characteristics such as wrinkles in the palm while images acquired using light of a second polarization at a second time show deeper characteristics such as veins. Within the images, the palm is identified and subdivided into sub-images. The sub-images are subsequently processed to determine feature vectors present in each sub-image. A current signature is determined using the feature vectors. A user may be identified based on a comparison of the current signature with a previously stored reference signature that is associated with a user identifier.
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公开(公告)号：US11900711B1
公开(公告)日：2024-02-13
申请号：US17075926
申请日：2020-10-21
发明人： Dilip Kumar , Manoj Aggarwal , George Leifman , Gerard Guy Medioni , Nikolai Orlov , Natan Peterfreund , Korwin Jon Smith , Dmitri Veikherman , Sora Kim
CPC分类号： G06V40/1318 , G06N3/045 , G06V40/1347 , G06T2207/20084 , G06V40/1341
摘要： An identification system includes one or more infrared light sources and a camera that acquires images of a user's palm. For example, at a first time, one or more first images may be acquired by the camera using infrared light with a first polarization that represent external characteristics of the user's palm. At a second time, one or more second images may be acquired using infrared light with a second polarization that represent internal characteristics of the user's palm. These images are processed to determine a first set of feature vectors and a second set of feature vectors. A current signature may be determined using the first set of feature vectors and the second set of feature vectors. In addition, a user may be identified based on a comparison of the current signature and previously stored reference signatures that are associated with candidate user identifiers.
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公开(公告)号：US11823488B1
公开(公告)日：2023-11-21
申请号：US17215762
申请日：2021-03-29
CPC分类号： G06V40/1365 , G06N3/08 , G06V40/1318
摘要： Biometric input, such as an image of a hand, may be processed to determine embedding vector data that may be used to identify users. Accuracy of the identification is improved by using high resolution inputs to a deep convolutional neural network (DCNN) that is trained to generate the embedding vector data that is representative of features in the input. Training data sets are expensive to develop and thus may be relatively small. During training of the DCNN, confidence loss values corresponding to the entire input as well as particular patches or portions of the input are determined. These patch-wise confidence loss values mitigate potential overfitting during training of the DCNN and improve overall performance of the trained DCNN to determine embedding vector data suitable for identification.
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公开(公告)号：US11625947B1
公开(公告)日：2023-04-11
申请号：US16807976
申请日：2020-03-03
发明人： Manoj Aggarwal , Brad Musick , Gerard Guy Medioni , Rui Zhao , Zhen Han
摘要： Biometric input, such as images of a hand obtained by a biometric input device, may be used to identify a person. An attacker may attempt to gain access by presenting false biometric data with an artificial biometric model, such as a fake hand. During a suspected attack, the attacker is prompted for additional data. For example, email address, telephone number, payment information, and so forth. This provides additional information about the attack while prolonging the time spent by the attacker on the attack. Information explicitly indicating failure is delayed or not presented at all. Data associated with an attack is placed into an exclusion list and further analyzed to recognize and mitigate future attacks. A subsequent attempt that corresponds to exclusion data proceeds with presenting prompts, gathering further information and consuming more of the attacker's time and resources.
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公开(公告)号：US11756036B1
公开(公告)日：2023-09-12
申请号：US16714348
申请日：2019-12-13
IPC分类号： G06V40/12 , G06Q20/40 , G06V10/46 , G06V40/13 , G06F18/2321
CPC分类号： G06Q20/40145 , G06F18/2321 , G06V10/462 , G06V40/13 , G06V40/1359 , G06V40/1376
摘要： Techniques for an identity-verification system to analyze image data representing palms of users using a segmented, characteristic-based approach. The system may compare palm-feature data representing characteristics of a palm of a user (or “query palm”) with stored palm-feature data of palms for user profiles (or “stored palms”). For instance, the system may identify characteristics of the query palm having salient or discriminative features, and compare palm-feature data for those discriminative characteristics to palm-feature data representing corresponding characteristics of stored palms of enrolled users. Additionally, the system may compare characteristics of the query palm with corresponding characteristics of stored palms until the system is confident that the query palm corresponds to a stored palm of a user profile. By performing simpler characteristic-by-characteristic sameness verification tasks, the system may reduce the amount of time and computing resources utilized to verify an identity of a user as opposed to top-level, palm-identity verification.
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公开(公告)号：US11734949B1
公开(公告)日：2023-08-22
申请号：US17210170
申请日：2021-03-23
CPC分类号： G06V40/1365 , G06T7/74 , G06V40/107 , G06V40/117 , G06V40/1318 , G06T2207/30196
摘要： Images of a hand are obtained by a camera. These images may depict the fingers and palm of the user. A pose of the hand relative to the camera may vary due to rotation, translation, articulation of joints in the hand, and so forth. One or more canonical images are generated by mapping the images to a canonical model. A first embedding model is used to determine a first embedding vector representative of the palm as depicted in the canonical images. A second embedding model is used to determine a set of second embedding vectors, each representative of individual fingers as depicted in the canonical images. Embedding distances in the embedding space from the embedding vectors to a closest match of previously stored embedding vectors are multiplied together to determine an overall distance. If the overall distance is less than a threshold value, an identity of a user is asserted.
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公开(公告)号：US11017203B1
公开(公告)日：2021-05-25
申请号：US16446323
申请日：2019-06-19
摘要： This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system and updating enrollment data of these users over time. To enroll in the user-recognition system, the user may initially scan his or her palm. The resulting image data may later be used when the user requests to be identified by the system by again scanning his or her palm. However, because the characteristics of user palms may change over the time, the user-recognition system may continue to build more and more data for use in recognizing the user, in addition to removing older data that may no longer accurately represent current characteristics of respective user palms.
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公开(公告)号：US12131575B1
公开(公告)日：2024-10-29
申请号：US17663273
申请日：2022-05-13
发明人： Manoj Aggarwal , Gerard Guy Medioni , Rajeev Ranjan , Joshua Engelsma , Baomin Wang , Abhinav Kashyap , Dilip Kumar
CPC分类号： G06V40/1365 , G06V10/145 , G06V40/1318 , G06V40/1347 , G06V40/50 , G02B5/208 , G02B5/3025
摘要： A biometric identification system acquires a multimodal image. The system is trained to determine three embeddings: a first embedding associated with features present in a first modality, an intersection embedding associated with features present in both the first and a second modality, and an XOR embedding associated with features that are not shared between the first modality and the second modality. Once trained, the system may process a multimodal query image to determine query embedding data. Additional information, such as minutiae depicted in the multimodal query image may also be determined. The query embedding data, and in some implementations the additional information, may be compared with enrolled embedding data associated with a previously enrolled user. If the comparison exceeds a threshold value, an identity may be asserted.
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