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公开(公告)号:US20200344500A1
公开(公告)日:2020-10-29
申请号:US16946826
申请日:2020-07-08
Applicant: Google LLC
Inventor: Daniel Goldman , Jason Lawrence , Andrew Huibers , Andrew Ian Russell , Steven M. Seitz
IPC: H04N21/222 , H04N7/15 , H04N21/2187 , H04N21/2343 , H04N21/242 , H04N21/4223 , H04N21/43 , H04N21/61 , H04N21/854 , H04N21/2365 , H04N21/239 , H04N21/431 , H04N13/305 , G02B27/01 , G02F1/29 , H04N7/14 , H04R1/02 , H04R3/00
Abstract: An example telepresence terminal includes a display, an image sensor, an infrared emitter, and an infrared depth sensor. The terminal may determine image data using visible light emitted by the infrared emitter and captured by the image sensor and determine depth data using infrared light captured by the infrared depth sensor. The terminal may also communicate the depth data and the image data to a remote telepresence terminal and receive remote image data and remote depth data. The terminal may also generate a first display image using the lenticular display based on the remote image data that is viewable from a first viewing location and generate a second display image using the lenticular display based on the remote image data and the remote depth data that is viewable from a second viewing location.
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公开(公告)号:US20200320777A1
公开(公告)日:2020-10-08
申请号:US16837612
申请日:2020-04-01
Applicant: Google LLC
Inventor: Moustafa Meshry , Ricardo Martin Brualla , Sameh Khamis , Daniel Goldman , Hugues Hoppe , Noah Snavely , Rohit Pandey
Abstract: According to an aspect, a method for neural rerendering includes obtaining a three-dimensional (3D) model representing a scene of a physical space, where the 3D model is constructed from a collection of input images, rendering an image data buffer from the 3D model according to a viewpoint, where the image data buffer represents a reconstructed image from the 3D model, receiving, by a neural rerendering network, the image data buffer, receiving, by the neural rerendering network, an appearance code representing an appearance condition, and transforming, by the neural rerendering network, the image data buffer into a rerendered image with the viewpoint of the image data buffer and the appearance condition specified by the appearance code.
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公开(公告)号:US20200160585A1
公开(公告)日:2020-05-21
申请号:US16321962
申请日:2018-11-15
Applicant: GOOGLE LLC
Inventor: Daniel Goldman
Abstract: Techniques of smoothing surface normals in a texture mapping application involve generating smoothed normals from the perspective of each camera using to capture images for texture mapping. Along these lines, a camera used to capture an image for texture mapping is situated at an orientation relative to the geometrical object onto which a texture mapping computer maps the texture image. The texture mapping computer places a filter window centered at a point on the geometrical object. The texture mapping computer then generates, as the smoothed normal at that point, an average normal over points in the filter window. The average normals thus computed for each camera are then used in the weights of the weighted average that is the image value at that point.
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公开(公告)号:US12026914B2
公开(公告)日:2024-07-02
申请号:US17597428
申请日:2021-01-19
Applicant: Google LLC
Inventor: Supreeth Achar , Daniel Goldman
IPC: G06T7/80 , G06T7/73 , G06V10/48 , G06V10/60 , G06V10/75 , H04N13/246 , H04N23/56 , G06V10/774
CPC classification number: G06T7/80 , G06T7/74 , G06V10/48 , G06V10/60 , G06V10/751 , H04N13/246 , H04N23/56 , G06T2207/10012 , G06T2207/10048 , G06T2207/20081 , G06T2207/20084 , G06T2207/30244 , G06V10/774
Abstract: A method including capturing a first image of a real-world scene by a first camera sensitive to a first spectrum of light, the first camera having a first light source, capturing a second image of the real-world scene by a second camera sensitive to a second spectrum of light, the second camera having a second light source, identifying at least one feature in the first image, identifying, using a machine learning (ML) model, at least one feature in the second image that matches the at least one feature identified in the first image, mapping pixels in the first image and the second image to rays in a three-dimensional (3D) space based on the matched at least one feature, and calibrating the first camera and the second camera based on the mapping.
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公开(公告)号:US20220130111A1
公开(公告)日:2022-04-28
申请号:US17310678
申请日:2020-10-28
Applicant: Google LLC
Inventor: Ricardo Martin Brualla , Moustafa Meshry , Daniel Goldman , Rohit Kumar Pandey , Sofien Bouaziz , Ke Li
Abstract: Systems and methods are described for utilizing an image processing system with at least one processing device to perform operations including receiving a plurality of input images of a user, generating a three-dimensional mesh proxy based on a first set of features extracted from the plurality of input images and a second set of features extracted from the plurality of input images. The method may further include generating a neural texture based on a three-dimensional mesh proxy and the plurality of input images, generating a representation of the user including at least a neural texture, and sampling at least one portion of the neural texture from the three-dimensional mesh proxy. In response to providing the at least one sampled portion to a neural renderer, the method may include receiving, from the neural renderer, a synthesized image of the user that is previously not captured by the image processing system.
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公开(公告)号:US11227426B2
公开(公告)日:2022-01-18
申请号:US16321962
申请日:2018-11-15
Applicant: GOOGLE LLC
Inventor: Daniel Goldman
Abstract: Techniques of smoothing surface normals in a texture mapping application involve generating smoothed normals from the perspective of each camera using to capture images for texture mapping. Along these lines, a camera used to capture an image for texture mapping is situated at an orientation relative to the geometrical object onto which a texture mapping computer maps the texture image. The texture mapping computer places a filter window centered at a point on the geometrical object. The texture mapping computer then generates, as the smoothed normal at that point, an average normal over points in the filter window. The average normals thus computed for each camera are then used in the weights of the weighted average that is the image value at that point.
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公开(公告)号:US10750210B2
公开(公告)日:2020-08-18
申请号:US16443481
申请日:2019-06-17
Applicant: Google LLC
Inventor: Daniel Goldman , Jason Lawrence , Andrew Huibers , Andrew Ian Russell , Steven M. Seitz
IPC: H04N21/222 , H04N7/15 , H04N21/2187 , H04N21/2343 , H04N21/242 , H04N21/4223 , H04N21/43 , H04N21/61 , H04N21/854 , H04N21/2365 , H04N21/239 , H04N21/431 , H04N13/305 , G02B27/01 , G02F1/29 , H04N7/14 , H04R1/02 , H04R3/00 , H04N21/41
Abstract: An example telepresence terminal includes a lenticular display, an image sensor, an infrared emitter, and an infrared depth sensor. The terminal may determine image data using visible light emitted by the infrared emitter and captured by the image sensor and determine depth data using infrared light captured by the infrared depth sensor. The terminal may also communicate the depth data and the image data to a remote telepresence terminal and receive remote image data and remote depth data. The terminal may also generate a first display image using the lenticular display based on the remote image data that is viewable from a first viewing location and generate a second display image using the lenticular display based on the remote image data and the remote depth data that is viewable from a second viewing location.
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