公开(公告)号：US12300020B1

公开(公告)日：2025-05-13

申请号：US17809237

申请日：2022-06-27

Applicant: AMAZON TECHNOLOGIES, INC.

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

IPC: G06V40/12 ,  G06F21/32 ,  G06V40/10

Abstract: A user performs an enrollment process to utilize a biometric identification system. This includes acquisition of biometric input data. Accuracy of subsequent identification is improved by utilizing high quality input data during enrollment. Input data is processed using a plurality of embedding models to determine a plurality of embedding vectors. These embedding vectors are translated into a common embedding space. Input quality may be determined based on analysis of these embedding vectors. For example, if a mean distance of the translated embedding vectors is less than a threshold value, the input data may be deemed to be of sufficient quality for use to complete an enrollment process. This analysis may also be used for post-enrollment operation, such as during an identification process to determine query input data that is of insufficient quality.

公开(公告)号：US11816932B1

公开(公告)日：2023-11-14

申请号：US17361811

申请日：2021-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Zheng Tang ,  Lior Zamir ,  Prithviraj Banerjee ,  Manoj Aggarwal ,  Gerard Guy Medioni ,  Dilip Kumar

IPC: G06V40/50 ,  G06V40/12 ,  G06F18/23

CPC classification number: G06V40/50 ,  G06F18/23 ,  G06V40/1347 ,  G06V40/1365

Abstract: This disclosure describes techniques for identifying users that are enrolled for use of a user-recognition system and updating identification 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 periodically perform processes for updating the identification data stored in association with the user in order to maintain or increase an accuracy of the user-recognition system.

公开(公告)号：US11670104B1

公开(公告)日：2023-06-06

申请号：US17097707

申请日：2020-11-13

Applicant: AMAZON TECHNOLOGIES, INC.

Inventor： Lior Zamir ,  Miriam Farber ,  Igor Kviatkovsky ,  Nadav Israel Bhonker ,  Manoj Aggarwal ,  Gerard Guy Medioni

IPC: G06V10/46 ,  G06V40/10 ,  G06V40/13

CPC classification number: G06V40/11 ,  G06V10/469 ,  G06V40/13 ,  G06V40/117

Abstract: A scanner acquires a set of images of a hand of a user to facilitate identification. These images may vary, due to changes in relative position, pose, lighting, obscuring objects such as a sleeve, and so forth. A first neural network determines output data comprising a spatial mask and a feature map for individual images in the set. The output data for two or more images is combined to provide aggregate data that is representative of the two or more images. The aggregate data may then be processed using a second neural network, such as convolutional neural network, to determine an embedding vector. The embedding vector may be stored and associated with a user account. At a later time, images acquired from the scanner may be processed to produce an embedding vector that is compared to the stored embedding vector to identify a user at the scanner.

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.