Volumetric avatars from a phone scan

US2023245365A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2023245365-A1
Application numberUS-202218074346-A
CountryUS
Kind codeA1
Filing dateDec 2, 2022
Priority dateFeb 1, 2022
Publication dateAug 3, 2023
Grant date

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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Abstract

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A method for generating a subject avatar using a mobile phone scan is provided. The method includes receiving, from a mobile device, multiple images of a first subject, extracting multiple image features from the images of the first subject based on a set of learnable weights, inferring a three-dimensional model of the first subject from the image features and an existing three-dimensional model of a second subject, animating the three-dimensional model of the first subject based on an immersive reality application running on a headset used by a viewer, and providing, to a display on the headset, an image of the three-dimensional model of the first subject. A system and a non-transitory, computer-readable medium storing instructions to perform the above method, are also provided.

First claim

Opening claim text (preview).

What is claimed is: 1 . A computer-implemented method, comprising: receiving, from a mobile device, multiple images of a first subject; extracting multiple image features from the images of the first subject based on a set of learnable weights; inferring a three-dimensional model of the first subject from the image features and an existing three-dimensional model of a second subject; animating the three-dimensional model of the first subject based on an immersive reality application running on a headset used by a viewer; and providing, to a display on the headset, an image of the three-dimensional model of the first subject. 2 . The computer-implemented method of claim 1 , wherein receiving multiple images of the first subject comprises receiving at least a neutral expression image of the first subject. 3 . The computer-implemented method of claim 1 , wherein receiving multiple images of the first subject comprises receiving at least an expressive image of the first subject. 4 . The computer-implemented method of claim 1 , wherein receiving multiple images of the first subject comprises receiving a sequence of images collected by scanning the mobile device in a selected direction over the first subject. 5 . The computer-implemented method of claim 1 , wherein inferring a three-dimensional model of the first subject comprises biasing the three-dimensional model of the first subject along a direction selected for collecting the images of the second subject. 6 . The computer-implemented method of claim 1 , wherein to form a three-dimensional model of the first subject comprises masking a gaze direction in the three-dimensional model of the second subject and inserting a gaze direction of the first subject. 7 . The computer-implemented method of claim 1 , wherein the image features comprise an identity feature of the first subject, and to form the three-dimensional model of the first subject comprises replacing an identity feature of the second subject with the identity feature of the second subject. 8 . The computer-implemented method of claim 1 , wherein the image features comprise an expression feature of the first subject, and to form the three-dimensional model of the first subject comprises matching the expression feature of the first subject in a latent expression database. 9 . The computer-implemented method of claim 1 , wherein animating the three-dimensional model of the first subject comprises projecting the image features along a direction between the three-dimensional model of the first subject and a selected observation point for the viewer. 10 . The computer-implemented method of claim 1 , wherein animating the three-dimensional model of the first subject comprises including an illumination source for the three-dimensional model of the first subject based on the existing three-dimensional model of the second subject. 11 . A system, comprising: a memory storing multiple instructions; and one or more processors configured to execute the instructions to cause the system to perform operations, comprising: receive, from a mobile device, multiple images of a first subject; extract multiple image features from the images of the first subject based on a set of learnable weights; infer a three-dimensional model of the first subject from the image features and an existing three-dimensional model of a second subject; animate the three-dimensional model of the first subject based on an immersive application running on a headset used by a viewer; and provide, to a display on the headset, an image of the three-dimensional model of the first subject. 12 . The system of claim 11 , wherein to receive multiple images of the first subject the one or more processors are configured to receive at least a neutral expression image of the first subject. 13 . The system of claim 11 , wherein to receive multiple images of the first subject the one or more processors are configured to receive at least an expressive image of the first subject. 14 . The system of claim 11 , to receive multiple images of the first subject the one or more processors are configured to receive a sequence of images collected by scanning the mobile device in a selected direction over the first subject. 15 . The system of claim 11 , wherein to infer the three-dimensional model of the first subject the one or more processors are configured to bias the three-dimensional model of the first subject along a direction selected for collecting the images of the second subject. 16 . A computer-implemented method for training a model to provide a view of a subject to an auto stereoscopic display in a virtual reality headset, comprising: collecting, from a face of multiple subjects, multiple images according to a capture script; updating an identity encoder and an expression encoder in a three-dimensional face model; generating, with the three-dimensional face model, a synthetic view of a user along a pre-selected direction corresponding to a view of the user; and training the three-dimensional face model based on a difference between an image of the user provided by a mobile device, and the synthetic view of the user. 17 . The computer-implemented method of claim 16 , wherein collecting multiple images according to a capture script comprises collecting each of the images with a pre-selected illumination configuration. 18 . The computer-implemented method of claim 16 , wherein collecting multiple images according to a capture script comprises collecting images with different expressions for each subject. 19 . The computer-implemented method of claim 16 , wherein training the three-dimensional face model comprises using a metric for a geometric artifact of the three-dimensional face model based on an image of the user. 20 . The computer-implemented method of claim 16 , wherein training the three-dimensional face model comprises using a metric for an identity artifact of the three-dimensional face model.

Assignees

Inventors

Classifications

  • Shape modification · CPC title

  • Editing of three-dimensional [3D] images, e.g. changing shapes or colours, aligning objects or positioning parts · CPC title

  • from multiple images · CPC title

  • Face · CPC title

  • G06T13/40Primary

    of characters, e.g. humans, animals or virtual beings · CPC title

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What does patent US2023245365A1 cover?
A method for generating a subject avatar using a mobile phone scan is provided. The method includes receiving, from a mobile device, multiple images of a first subject, extracting multiple image features from the images of the first subject based on a set of learnable weights, inferring a three-dimensional model of the first subject from the image features and an existing three-dimensional mode…
Who is the assignee on this patent?
Meta Platforms Tech Llc
What technology area does this patent fall under?
Primary CPC classification G06T13/40. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Aug 03 2023 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 7 related publications on this page (citations in our corpus or others sharing the same primary CPC).