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公开(公告)号：USD985011S1
公开(公告)日：2023-05-02
申请号：US29709053
申请日：2019-10-10
Applicant: Google LLC
Designer： Michelle Chen , Ryan Geiss , Marc Levoy , Kelly Tsai , Chorong Johnston , Alexander Schiffhauer , Samuel Hasinoff
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公开(公告)号：US11210799B2
公开(公告)日：2021-12-28
申请号：US16652568
申请日：2017-12-05
Applicant: Google LLC
Inventor： David Jacobs , Rahul Garg , Yael Pritch Knaan , Neal Wadhwa , Marc Levoy
Abstract: A camera may capture an image of a scene and use the image to generate a first and a second subpixel image of the scene. The pair of subpixel images may be represented by a first set of subpixels and a second set of subpixels from the image respectively. Each pixel of the image may include two green subpixels that are respectively represented in the first and second subpixel images. The camera may determine a disparity between a portion of the scene as represented by the pair of subpixel images and may estimate a depth map of the scene that indicates a depth of the portion relative to other portions of the scene based on the disparity and a baseline distance between the two green subpixels. A new version of the image may be generated with a focus upon the portion and with the other portions of the scene blurred.
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公开(公告)号：US20210056349A1
公开(公告)日：2021-02-25
申请号：US17090948
申请日：2020-11-06
Applicant: Google LLC
Inventor： Yael Pritch Knaan , Marc Levoy , Neal Wadhwa , Rahul Garg , Sameer Ansari , Jiawen Chen
IPC: G06K9/62
Abstract: Apparatus and methods related to using machine learning to determine depth maps for dual pixel images of objects are provided. A computing device can receive a dual pixel image of at least a foreground object. The dual pixel image can include a plurality of dual pixels. A dual pixel of the plurality of dual pixels can include a left-side pixel and a right-side pixel that both represent light incident on a single dual pixel element used to capture the dual pixel image. The computing device can be used to train a machine learning system to determine a depth map associated with the dual pixel image. The computing device can provide the trained machine learning system.
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公开(公告)号：US20200226419A1
公开(公告)日：2020-07-16
申请号：US16246280
申请日：2019-01-11
Applicant: Google LLC
Inventor： Yael Pritch Knaan , Marc Levoy , Neal Wadhwa , Rahul Garg , Sameer Ansari , Jiawen Chen
IPC: G06K9/62
Abstract: Apparatus and methods related to using machine learning to determine depth maps for dual pixel images of objects are provided. A computing device can receive a dual pixel image of at least a foreground object. The dual pixel image can include a plurality of dual pixels. A dual pixel of the plurality of dual pixels can include a left-side pixel and a right-side pixel that both represent light incident on a single dual pixel element used to capture the dual pixel image. The computing device can be used to train a machine learning system to determine a depth map associated with the dual pixel image. The computing device can provide the trained machine learning system.
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公开(公告)号：US11599747B2
公开(公告)日：2023-03-07
申请号：US17090948
申请日：2020-11-06
Applicant: Google LLC
Inventor： Yael Pritch Knaan , Marc Levoy , Neal Wadhwa , Rahul Garg , Sameer Ansari , Jiawen Chen
IPC: G06K9/62
Abstract: Apparatus and methods related to using machine learning to determine depth maps for dual pixel images of objects are provided. A computing device can receive a dual pixel image of at least a foreground object. The dual pixel image can include a plurality of dual pixels. A dual pixel of the plurality of dual pixels can include a left-side pixel and a right-side pixel that both represent light incident on a single dual pixel element used to capture the dual pixel image. The computing device can be used to train a machine learning system to determine a depth map associated with the dual pixel image. The computing device can provide the trained machine learning system.
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Patent Agency Ranking
公开(公告)号：US20220076018A1
公开(公告)日：2022-03-10
申请号：US17299188
申请日：2019-01-15
Applicant: Google LLC
Inventor： Ryan Geiss , Ruiduo Yang , Marc Levoy
Abstract: Apparatus and methods related to photography are provided. A computing device can receive an input image. An object detector of the computing device can determine an object region of interest of the input image that is associated with an object detected in the input image. A trained machine learning algorithm can determine an output photographic region of interest for the input image based on the object region of interest and the input image. The machine learning algorithm can be trained to identify an output photographic region of interest that is suitable for use by a photographic function for image generation. The computing device can generate an output related to the output photographic region of interest.
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公开(公告)号：US20200242788A1
公开(公告)日：2020-07-30
申请号：US16652568
申请日：2017-12-05
Applicant: Google LLC
Inventor： David Jacobs , Rahul Garg , Yael Pritch Knaan , Neal Wadhwa , Marc Levoy
Abstract: A camera may capture an image of a scene and use the image to generate a first and a second subpixel image of the scene. The pair of subpixel images may be represented by a first set of subpixels and a second set of subpixels from the image respectively. Each pixel of the image may include two green subpixels that are respectively represented in the first and second subpixel images. The camera may determine a disparity between a portion of the scene as represented by the pair of subpixel images and may estimate a depth map of the scene that indicates a depth of the portion relative to other portions of the scene based on the disparity and a baseline distance between the two green subpixels. A new version of the image may be generated with a focus upon the portion and with the other portions of the scene blurred.
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公开(公告)号：US20240395035A1
公开(公告)日：2024-11-28
申请号：US18790932
申请日：2024-07-31
Applicant: Google LLC
Inventor： Ryan Geiss , Ruido Yang , Marc Levoy
Abstract: Apparatus and methods related to photography are provided. A computing device can receive an input image. An object detector of the computing device can determine an object region of interest of the input image that is associated with an object detected in the input image. A trained machine learning algorithm can determine an output photographic region of interest for the input image based on the object region of interest and the input image. The machine learning algorithm can be trained to identify an output photographic region of interest that is suitable for use by a photographic function for image generation. The computing device can generate an output related to the output photographic region of interest.
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公开(公告)号：US12056925B2
公开(公告)日：2024-08-06
申请号：US17299188
申请日：2019-01-15
Applicant: Google LLC
Inventor： Ryan Geiss , Ruiduo Yang , Marc Levoy
CPC classification number: G06V20/35 , G06N20/00 , G06V10/56 , H04N23/80 , G06T2207/20081 , G06T2207/20084
Abstract: Apparatus and methods related to photography are provided. A computing device can receive an input image. An object detector of the computing device can determine an object region of interest of the input image that is associated with an object detected in the input image. A trained machine learning algorithm can determine an output photographic region of interest for the input image based on the object region of interest and the input image. The machine learning algorithm can be trained to identify an output photographic region of interest that is suitable for use by a photographic function for image generation. The computing device can generate an output related to the output photographic region of interest.
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公开(公告)号：US10860889B2
公开(公告)日：2020-12-08
申请号：US16246280
申请日：2019-01-11
Applicant: Google LLC
Inventor： Yael Pritch Knaan , Marc Levoy , Neal Wadhwa , Rahul Garg , Sameer Ansari , Jiawen Chen
IPC: G06K9/62
Abstract: Apparatus and methods related to using machine learning to determine depth maps for dual pixel images of objects are provided. A computing device can receive a dual pixel image of at least a foreground object. The dual pixel image can include a plurality of dual pixels. A dual pixel of the plurality of dual pixels can include a left-side pixel and a right-side pixel that both represent light incident on a single dual pixel element used to capture the dual pixel image. The computing device can be used to train a machine learning system to determine a depth map associated with the dual pixel image. The computing device can provide the trained machine learning system.
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