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公开(公告)号：US20240153116A1
公开(公告)日：2024-05-09
申请号：US17981891
申请日：2022-11-07
Applicant: Google LLC
Inventor： Kuntal Sengupta , Adarsh Kowdle , Andrey Zhmoginov , Hart Levy
CPC classification number: G06T7/521 , G06F21/32 , G06V40/172 , G06V40/40 , G06T2207/10048 , G06T2207/20081 , G06T2207/30201
Abstract: Provided are computing systems, methods, and platforms for using machine-learned models to generate a depth map. The operations can include projecting, using a dot illuminator, near-infrared (NIR) dots on the scene. The NIR dots can have a uniform pattern. Additionally, the operations can include capturing, using a single NIR camera, the projected NIR dots on the scene. Moreover, the operations can include generating a dot image based on the captured NIR dots on the scene. Furthermore, the operations can include processing the dot image with a machine-learned model to generate a depth map of the scene. Subsequently, the operations can further include evaluating the generated depth map of the scene and a ground truth depth map, and performing an action based on the evaluation.
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2.发明申请公开(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
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.
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3.发明授权公开(公告)号：US11694433B2
公开(公告)日：2023-07-04
申请号：US17421505
申请日：2019-02-15
Applicant: Google LLC
Inventor： Wen-Sheng Chu , Kuntal Sengupta
IPC: G06K9/00 , G06V20/10 , G06T7/521 , G06T7/73 , G06V10/141 , G06V10/94 , G06V10/22 , G06F18/22 , H04N23/56
CPC classification number: G06V20/10 , G06F18/22 , G06T7/521 , G06T7/73 , G06V10/141 , G06V10/22 , G06V10/95 , H04N23/56 , G06T2207/10048 , G06T2207/20084
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.
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Patent Agency Ranking
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
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.
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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.
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.
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公开(公告)号：US11205064B1
公开(公告)日：2021-12-21
申请号：US16901564
申请日：2020-06-15
Applicant: Google LLC
Inventor： Wen-Sheng Chu , Sam Ekong , Kuntal Sengupta
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.
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公开(公告)号：US12183117B2
公开(公告)日：2024-12-31
申请号：US17433912
申请日：2019-04-03
Applicant: Google LLC
Inventor： Cem Kemal Hamami , Joseph Edwin Johnson, Jr. , Kuntal Sengupta , Piotr Kulaga , Wen-Sheng Chu , Zachary Iqbal
Abstract: A method includes receiving data indicative of an image of a face of an unknown user of the computing device while the computing device is in a reduced access mode locked state. The method also includes determining whether the unknown user is the known user by at least comparing the image of the face of the unknown user to one or more images of a plurality of images of a face of a known user of the computing device. The method further includes setting the computing device to an increased access mode in response to determining that the unknown user is the known user.
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公开(公告)号：US20220139109A1
公开(公告)日：2022-05-05
申请号：US17433912
申请日：2019-04-03
Applicant: Google LLC
Inventor： Cem Kemal Hamami , Joseph Edwin Johnson, Jr. , Kuntal Sengupta , Piotr Kulaga , Wen-Sheng Chu , Zachary Iqbal
Abstract: A method includes receiving data indicative of an image of a face of an unknown user of the computing device while the computing device is in a reduced access mode locked state. The method also includes determining whether the unknown user is the known user by at least comparing the image of the face of the unknown user to one or more images of a plurality of images of a face of a known user of the computing device. The method further includes setting the computing device to an increased access mode in response to determining that the unknown user is the known user.
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