公开(公告)号：US20220335638A1

公开(公告)日：2022-10-20

申请号：US17596794

申请日：2021-04-19

Applicant: Google LLC

Inventor： Abhishek Kar ,  Hossam Isack ,  Adarsh Prakash Murthy Kowdle ,  Aveek Purohit ,  Dmitry Medvedev

IPC: G06T7/593 ,  G06T7/285

Abstract: According to an aspect, a method for depth estimation includes receiving image data from a sensor system, generating, by a neural network, a first depth map based on the image data, where the first depth map has a first scale, obtaining depth estimates associated with the image data, and transforming the first depth map to a second depth map using the depth estimates, where the second depth map has a second scale.

公开(公告)号：US12260572B2

公开(公告)日：2025-03-25

申请号：US17907529

申请日：2021-08-05

Applicant: Google LLC

Inventor： Varun Jampani ,  Huiwen Chang ,  Kyle Sargent ,  Abhishek Kar ,  Richard Tucker ,  Dominik Kaeser ,  Brian L. Curless ,  David Salesin ,  William T. Freeman ,  Michael Krainin ,  Ce Liu

IPC: G06T7/00 ,  G06T5/60 ,  G06T5/77 ,  G06T7/50

Abstract: A method includes determining, based on an image having an initial viewpoint, a depth image, and determining a foreground visibility map including visibility values that are inversely proportional to a depth gradient of the depth image. The method also includes determining, based on the depth image, a background disocclusion mask indicating a likelihood that pixel of the image will be disoccluded by a viewpoint adjustment. The method additionally includes generating, based on the image, the depth image, and the background disocclusion mask, an inpainted image and an inpainted depth image. The method further includes generating, based on the depth image and the inpainted depth image, respectively, a first three-dimensional (3D) representation of the image and a second 3D representation of the inpainted image, and generating a modified image having an adjusted viewpoint by combining the first and second 3D representation based on the foreground visibility map.

公开(公告)号：US20240249422A1

公开(公告)日：2024-07-25

申请号：US17907529

申请日：2021-08-05

Applicant: Google LLC

Inventor： Varun Jampani ,  Huiwen Chang ,  Kyle Sargent ,  Abhishek Kar ,  Richard Tucker ,  Dominik Kaeser ,  Brian L. Curless ,  David Salesin ,  William T. Freeman ,  Michael Krainin ,  Ce Liu

IPC: G06T7/50 ,  G06T5/60 ,  G06T5/77

CPC classification number: G06T7/50 ,  G06T5/60 ,  G06T5/77 ,  G06T2207/20081

Abstract: A method includes determining, based on an image having an initial viewpoint, a depth image, and determining a foreground visibility map including visibility values that are inversely proportional to a depth gradient of the depth image. The method also includes determining, based on the depth image, a background disocclusion mask indicating a likelihood that pixel of the image will be disoccluded by a viewpoint adjustment. The method additionally includes generating, based on the image, the depth image, and the background disocclusion mask, an inpainted image and an inpainted depth image. The method further includes generating, based on the depth image and the inpainted depth image, respectively, a first three-dimensional (3D) representation of the image and a second 3D representation of the inpainted image, and generating a modified image having an adjusted viewpoint by combining the first and second 3D representation based on the foreground visibility map.

公开(公告)号：US20230236219A1

公开(公告)日：2023-07-27

申请号：US17648572

申请日：2022-01-21

Applicant: GOOGLE LLC

Inventor： Yunwen Zhou ,  Ryan Christopher DuToit ,  Abhishek Kar ,  Konstantine Nicholas John Tsotsos ,  Eric Turner ,  Chao Guo

IPC: G01P21/00 ,  G06T7/50 ,  G06T7/80 ,  G06T7/33 ,  G06T7/20 ,  G01P13/00 ,  G01P15/08

CPC classification number: G01P21/00 ,  G06T7/50 ,  G06T7/80 ,  G06T7/33 ,  G06T7/20 ,  G01P13/00 ,  G01P15/08 ,  G06T2207/20084

Abstract: Disclosed is a method including receiving a depth map estimated using data based on image and data received from a movement sensor as input, generating an alignment parameter based on the depth map, adding the alignment parameter to a pre-calibration state to define a user operational calibration state, generating scale parameters and shift parameters based on features associated with the data received from the image and movement sensor, and calibrating the image and movement sensor based on the user operational calibration state, the scale parameters and the shift parameters.