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    Correlation-Based Object Anti-Spoofing for Dual-Pixel Cameras
    1.
    发明申请
    Correlation-Based Object Anti-Spoofing for Dual-Pixel Cameras 有权

    公开(公告)号：US20250029424A1

    公开(公告)日：2025-01-23

    申请号：US18549547

    申请日：2022-04-01

    Applicant: Google LLC

    Inventor： Siyuan Qiao ,  Wen-Sheng Chu

    IPC: G06V40/40 ,  G06F21/32 ,  G06V10/74

    Abstract: A method includes obtaining dual-pixel image data that represents an object and includes a first sub-image and a second sub-image, and generating (i) a first feature map based on the first sub-image and (ii) a second feature map based on the second sub-image. The method also includes generating a correlation volume by determining, for each respective offset of a plurality of offsets between the first feature map and the second feature map, pixel-wise similarities between (i) the first feature map and (ii) the second feature map offset from the first feature map by the respective offset. The method further includes determining, by an anti-spoofing model and based on the correlation volume, a spoofing value indicative of a likelihood that the object represented by the dual-pixel image data is being spoofed.

    Detection of Projected Infrared Patterns Using Difference of Gaussian and Blob Identification
    3.
    发明申请
    Detection of Projected Infrared Patterns Using Difference of Gaussian and Blob Identification 有权

    公开(公告)号：US20220083775A1

    公开(公告)日：2022-03-17

    申请号：US17421505

    申请日：2019-02-15

    Applicant: Google LLC

    Inventor： Wen-Sheng Chu ,  Kuntal Sengupta

    IPC: G06K9/00 ,  G06T7/73 ,  G06K9/20 ,  G06K9/62 ,  H04N5/225 ,  G06T7/521

    Abstract: A method may include obtaining an infrared image of an object and determining a difference of Gaussian image that represents features of the infrared image that have spatial frequencies within a spatial frequency range defined by a first Gaussian operator and a second Gaussian operator. The method may also include identifying one or more blob regions within the difference of Gaussian image. Each blob region of the one or more blob regions includes a region of connected pixels in the difference of Gaussian image. The method may further include, based on identifying the one or more blob regions within the difference of Gaussian image, determining that the infrared image represents the object illuminated by a pattern projected onto the object by an infrared projector.

    Measuring Quality of Depth Images in Real Time
    8.
    发明申请
    Measuring Quality of Depth Images in Real Time 有权

    公开(公告)号：US20210390286A1

    公开(公告)日：2021-12-16

    申请号：US16901564

    申请日：2020-06-15

    Applicant: Google LLC

    Inventor： Wen-Sheng Chu ,  Sam Ekong ,  Kuntal Sengupta

    IPC: G06K9/00 ,  G01B11/22 ,  G06K9/46

    Abstract: Methods are provided to determine a quality score for depth map. The quality score is calculated from metrics that detect artifacts or other inaccuracies in the depth map such as flat patches, artifactual edges, and patchy regions. A flatness metric detects regions of neighboring pixels that have substantially the same depth value. A jaggedness metric detects hard edges or other discontinuities. A patchiness metric detects regions that are wholly enclosed by an edge and that have sub-threshold areas. The individual metrics are normalized and combined to determine an overall quality score for the depth map. The quality score can then be compared to one or more thresholds to determine a quality label for the depth map. Such a quality label can then be used to unlock a device, to invalidate an unlock attempt, to recalibrate a depth sensor, or to perform some other operations.

    SEAMLESS DRIVER AUTHENTICATION USING AN IN-VEHICLE CAMERA IN CONJUNCTION WITH A TRUSTED MOBILE COMPUTING DEVICE
    9.
    发明申请
    SEAMLESS DRIVER AUTHENTICATION USING AN IN-VEHICLE CAMERA IN CONJUNCTION WITH A TRUSTED MOBILE COMPUTING DEVICE 有权

    公开(公告)号：US20210229673A1

    公开(公告)日：2021-07-29

    申请号：US16764322

    申请日：2019-11-12

    Applicant: Google LLC

    Inventor： Hanumant Prasad R Singh ,  Piotr Kulaga ,  Wen-Sheng Chu ,  Kuntal Sengupta ,  Joseph Edwin Johnson Jr.

    IPC: B60W40/08 ,  G06K9/00

    Abstract: An example method includes establishing, by a mobile computing device, a connection with a vehicle computing system of a vehicle, receiving, from the vehicle computing system, feature data associated with at least one image of a face of a user of the vehicle, wherein the at least one image of the face is captured by an image capture device included in the vehicle, determining, based on a comparison between the feature data associated with the at least one image of the face of the user and feature data of at least one image of a face of a previously enrolled user, a match between the user of the vehicle and the previously enrolled user, authenticating, based on the match, the user of the vehicle, and sending, to the vehicle computing system, authentication data for the user of the vehicle, wherein the authentication data is indicative of the match.

    Continuous Personalization of Face Authentication
    10.
    发明申请
    Continuous Personalization of Face Authentication 有权

    公开(公告)号：US20250095406A1

    公开(公告)日：2025-03-20

    申请号：US18970431

    申请日：2024-12-05

    Applicant: Google LLC

    Inventor： Cem Kemal Hamami ,  Philip Andrew Mansfield ,  Samuel Paradis ,  Michael Williams ,  Wen-Sheng Chu

    IPC: G06V40/50 ,  G06V10/762 ,  G06V40/16

    Abstract: This document describes systems and techniques that enable continuous personalization of face authentication. In aspects, an authentication system associated with a network includes an authentication manager. The authentication manager receives an embedding representing image data associated with a user's face. The authentication manager generates a confidence score based on the embedding. Further, the authentication manager updates previously enrolled embeddings with the embedding based on the confidence score, the embedding meeting a clustering confidence threshold. Through such a technique, the authentication manager can alter the previously enrolled embeddings by which a future embedding is used to authenticate the user's face. By so doing, the techniques may provide more-accurate and successful user authentication over time.

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