公开(公告)号：US11823488B1

公开(公告)日：2023-11-21

申请号：US17215762

申请日：2021-03-29

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Rajeev Ranjan ,  Manoj Aggarwal ,  Gerard Guy Medioni

IPC: G06V40/12 ,  G06N3/08 ,  G06V40/13

CPC classification number: G06V40/1365 ,  G06N3/08 ,  G06V40/1318

Abstract: 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.

公开(公告)号：US11625947B1

公开(公告)日：2023-04-11

申请号：US16807976

申请日：2020-03-03

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Manoj Aggarwal ,  Brad Musick ,  Gerard Guy Medioni ,  Rui Zhao ,  Zhen Han

IPC: G06K9/00 ,  G06V40/12 ,  G06V40/50 ,  G06V40/13

Abstract: 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.

公开(公告)号：US12230052B1

公开(公告)日：2025-02-18

申请号：US16712655

申请日：2019-12-12

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Igor Kviatkovsky ,  Nadav Israel Bhonker ,  Yevgeni Nogin ,  Roman Goldenberg ,  Manoj Aggarwal ,  Gerard Guy Medioni

IPC: G06K9/00 ,  G06F18/2131 ,  G06F18/214 ,  G06K9/62 ,  G06T3/00 ,  G06T3/04 ,  G06T7/70 ,  G06V40/12

Abstract: Images of a hand are obtained by a camera. A pose of the hand relative to the camera may vary due to rotation, translation, articulation of joints in the hand, and so forth. Avatars comprising texture maps from images of actual hands and three-dimensional models that describe the shape of those hands are manipulated into different poses and articulations to produce synthetic images. Given that the mapping of points on an avatar to the synthetic image is known, highly accurate annotation data is produced that relates particular points on the avatar to the synthetic image. An artificial neural network (ANN) is trained using the synthetic images and corresponding annotation data. The trained ANN processes a first image of a hand to produce a second image of the hand that appears to be in a standardized or canonical pose. The second image may then be processed to identify the user.

公开(公告)号：US12131575B1

公开(公告)日：2024-10-29

申请号：US17663273

申请日：2022-05-13

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Manoj Aggarwal ,  Gerard Guy Medioni ,  Rajeev Ranjan ,  Joshua Engelsma ,  Baomin Wang ,  Abhinav Kashyap ,  Dilip Kumar

IPC: G06V40/12 ,  G02B5/20 ,  G02B5/30 ,  G06V10/145 ,  G06V40/13 ,  G06V40/50

CPC classification number: G06V40/1365 ,  G06V10/145 ,  G06V40/1318 ,  G06V40/1347 ,  G06V40/50 ,  G02B5/208 ,  G02B5/3025

Abstract: 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.

公开(公告)号：US12086225B1

公开(公告)日：2024-09-10

申请号：US17448437

申请日：2021-09-22

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Gerard Guy Medioni ,  Manoj Aggarwal ,  Alon Shoshan ,  Igor Kviatkovsky ,  Nadav Israel Bhonker ,  Lior Zamir ,  Dilip Kumar

IPC: G06F21/32 ,  G06F18/213 ,  G06F18/214 ,  G06F21/62

CPC classification number: G06F21/32 ,  G06F18/213 ,  G06F18/214 ,  G06F21/6245

Abstract: An image of at least a portion of a user during enrollment to a biometric identification system is acquired and processed with a first model to determine a first embedding that is representative of features in that image in a first embedding space. The first embedding may be stored for later comparison to identify the user, while the image is not stored. A second model that uses a second embedding space may be later developed. A transformer is trained to accept as input an embedding from the first model and produce as output an embedding consistent with the second embedding space. The previously stored first embedding may be converted to a second embedding in a second embedding space using the transformer. As a result, new embedding models may be implemented without requiring storage of user images for later reprocessing with the new models or requiring re-enrollment by users.

公开(公告)号：US11868443B1

公开(公告)日：2024-01-09

申请号：US17302770

申请日：2021-05-12

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Rajeev Ranjan ,  Prithviraj Banerjee ,  Manoj Aggarwal ,  Gerard Guy Medioni ,  Dilip Kumar

IPC: G06F18/2431 ,  G06N3/08 ,  G06F18/214 ,  G06F18/2113 ,  G06N3/045

CPC classification number: G06F18/2431 ,  G06F18/214 ,  G06F18/2113 ,  G06N3/045 ,  G06N3/08

Abstract: A neural network is trained to process input data and generate a classification value that characterizes the input with respect to an ordered continuum of classes. For example, the input data may comprise an image and the classification value may be indicative of a quality of the image. The ordered continuum of classes may represent classes of quality of the image ranging from “worst”, “bad”, “normal”, “good”, to “best”. During training, loss values are determined using an ordered classification loss function. The ordered classification loss function maintains monotonicity in the loss values that corresponds to placement in the continuum. For example, the classification value for a “bad” image will be less than the classification value indicative of a “best” image. The classification value may be used for subsequent processing. For example, biometric input data may be required to have a minimum classification value for further processing.

公开(公告)号：US11705133B1

公开(公告)日：2023-07-18

申请号：US16212318

申请日：2018-12-06

Applicant: Amazon Technologies, Inc.

Inventor： Manoj Aggarwal ,  Dmitri Veikherman

IPC: G10L15/00 ,  G10L17/00 ,  G06Q30/0601 ,  G10L17/06 ,  G06V40/16

CPC classification number: G10L17/00 ,  G06Q30/0641 ,  G06V40/172 ,  G10L17/06

Abstract: This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system. To be identified using the user-recognition system, a user may first enroll in the system by stating an utterance at a first device having a first microphone. In response, the first microphone may generate first audio data. Later, when the user would like to be identified by the system, the user may state the utterance again, although this time to a second device having a second microphone. This second microphone may accordingly generate second audio data. Because the acoustic response of the first microphone may differ from the acoustic response of the second microphone, however, this disclosure describes techniques to apply a relative transfer function to one or both of the first or second audio data prior to comparing these data so as to increase the recognition accuracy of the system.

公开(公告)号：US11527092B1

公开(公告)日：2022-12-13

申请号：US17099074

申请日：2020-11-16

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Miriam Farber ,  Manoj Aggarwal ,  Gerard Guy Medioni

IPC: G06V40/10 ,  G06T5/20 ,  G06T5/00 ,  G06N3/08 ,  G06N3/04

Abstract: Images of a hand may be used to identify users. Quality, detail, and so forth of these images may vary. An image is processed to determine a first spatial mask. A first neural network comprising many layers uses the first spatial mask at a first layer and a second spatial mask at a second layer to process images and produce an embedding vector representative of features in the image. The first spatial mask provides information about particular portions of the input image, and is determined by processing the image with an algorithm such as an orientation certainty level (OCL) algorithm. The second spatial mask is determined using unsupervised training and represents weights of particular portions of the input image as represented at the second layer. The use of the masks allows the first neural network to learn to use or disregard particular portions of the image, improving overall accuracy.

公开(公告)号：US11288490B1

公开(公告)日：2022-03-29

申请号：US17154818

申请日：2021-01-21

Applicant: Amazon Technologies, Inc.

Inventor： Manoj Aggarwal ,  Jason Garfield ,  Korwin Jon Smith ,  Jordan Tyler Williams

IPC: G06K9/00 ,  G06K9/62

Abstract: 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.

公开(公告)号：US12236709B1

公开(公告)日：2025-02-25

申请号：US17706107

申请日：2022-03-28

Applicant: Amazon Technologies, Inc.

Inventor： Manoj Aggarwal ,  Jason Garfield ,  Korwin Jon Smith ,  Jordan Tyler Williams

IPC: G06V40/13 ,  G06F18/22 ,  G06V40/12

Abstract: 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.