公开(公告)号：US11042729B2

公开(公告)日：2021-06-22

申请号：US15831823

申请日：2017-12-05

Applicant: Google LLC

Inventor： Avneesh Sud ,  Steven Hickson ,  Vivek Kwatra ,  Nicholas Dufour

IPC: G06K9/00 ,  A61B5/16 ,  G06N3/08 ,  G06N3/04 ,  H04N5/232 ,  G06K9/62 ,  G06F3/01 ,  A61B5/00 ,  G01S3/00 ,  G06K9/46 ,  H04N13/344

Abstract: Images of a plurality of users are captured concurrently with the plurality of users evincing a plurality of expressions. The images are captured using one or more eye tracking sensors implemented in one or more head mounted devices (HMDs) worn by the plurality of first users. A machine learnt algorithm is trained to infer labels indicative of expressions of the users in the images. A live image of a user is captured using an eye tracking sensor implemented in an HMD worn by the user. A label of an expression evinced by the user in the live image is inferred using the machine learnt algorithm that has been trained to predict labels indicative of expressions. The images of the users and the live image can be personalized by combining the images with personalization images of the users evincing a subset of the expressions.

公开(公告)号：US20180314881A1

公开(公告)日：2018-11-01

申请号：US15831823

申请日：2017-12-05

Applicant: Google LLC

Inventor： Avneesh Sud ,  Steven Hickson ,  Vivek Kwatra ,  Nicholas Dufour

IPC: G06K9/00 ,  A61B5/16 ,  G06N3/08 ,  G06N3/04 ,  H04N5/232 ,  G06F3/01 ,  G06K9/62

Abstract: Images of a plurality of users are captured concurrently with the plurality of users evincing a plurality of expressions. The images are captured using one or more eye tracking sensors implemented in one or more head mounted devices (HMDs) worn by the plurality of first users. A machine learnt algorithm is trained to infer labels indicative of expressions of the users in the images. A live image of a user is captured using an eye tracking sensor implemented in an HMD worn by the user. A label of an expression evinced by the user in the live image is inferred using the machine learnt algorithm that has been trained to predict labels indicative of expressions. The images of the users and the live image can be personalized by combining the images with personalization images of the users evincing a subset of the expressions.

公开(公告)号：US20250032045A1

公开(公告)日：2025-01-30

申请号：US18792056

申请日：2024-08-01

Applicant: Google LLC

Inventor： Avneesh Sud ,  Steven Hickson ,  Vivek Kwatra ,  Nicholas Dufour

IPC: A61B5/00 ,  A61B5/16 ,  G01S3/00 ,  G06F3/01 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G06V20/20 ,  G06V40/16 ,  G06V40/19 ,  H04N13/344 ,  H04N23/60 ,  H04N23/611

Abstract: Images of a plurality of users are captured concurrently with the plurality of users evincing a plurality of expressions. The images are captured using one or more eye tracking sensors implemented in one or more head mounted devices (HMDs) worn by the plurality of first users. A machine learnt algorithm is trained to infer labels indicative of expressions of the users in the images. A live image of a user is captured using an eye tracking sensor implemented in an HMD worn by the user. A label of an expression evinced by the user in the live image is inferred using the machine learnt algorithm that has been trained to predict labels indicative of expressions. The images of the users and the live image can be personalized by combining the images with personalization images of the users evincing a subset of the expressions.

公开(公告)号：US20210295025A1

公开(公告)日：2021-09-23

申请号：US17339128

申请日：2021-06-04

Applicant: Google LLC

Inventor： Avneesh Sud ,  Steven Hickson ,  Vivek Kwatra ,  Nicholas Dufour

IPC: G06K9/00 ,  A61B5/16 ,  G06N3/08 ,  G06N3/04 ,  H04N5/232 ,  G06K9/62 ,  G06F3/01 ,  A61B5/00 ,  G01S3/00 ,  G06K9/46

Abstract: Images of a plurality of users are captured concurrently with the plurality of users evincing a plurality of expressions. The images are captured using one or more eye tracking sensors implemented in one or more head mounted devices (HMDs) worn by the plurality of first users. A machine learnt algorithm is trained to infer labels indicative of expressions of the users in the images. A live image of a user is captured using an eye tracking sensor implemented in an HMD worn by the user. A label of an expression evinced by the user in the live image is inferred using the machine learnt algorithm that has been trained to predict labels indicative of expressions. The images of the users and the live image can be personalized by combining the images with personalization images of the users evincing a subset of the expressions.

公开(公告)号：US12053301B2

公开(公告)日：2024-08-06

申请号：US17339128

申请日：2021-06-04

Applicant: Google LLC

Inventor： Avneesh Sud ,  Steven Hickson ,  Vivek Kwatra ,  Nicholas Dufour

IPC: A61B5/00 ,  A61B5/16 ,  G01S3/00 ,  G06F3/01 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06V10/44 ,  G06V10/764 ,  G06V10/82 ,  G06V20/20 ,  G06V40/16 ,  H04N23/60 ,  H04N23/611 ,  G06V40/19 ,  H04N13/344

CPC classification number: A61B5/6803 ,  A61B5/165 ,  G01S3/00 ,  G06F3/013 ,  G06F18/214 ,  G06F18/2413 ,  G06N3/04 ,  G06N3/045 ,  G06N3/08 ,  G06V10/454 ,  G06V10/764 ,  G06V10/82 ,  G06V20/20 ,  G06V40/174 ,  H04N23/60 ,  H04N23/611 ,  A61B5/163 ,  A61B5/7267 ,  A61B5/7275 ,  G06V40/19 ,  H04N13/344

Abstract: Images of a plurality of users are captured concurrently with the plurality of users evincing a plurality of expressions. The images are captured using one or more eye tracking sensors implemented in one or more head mounted devices (HMDs) worn by the plurality of first users. A machine learnt algorithm is trained to infer labels indicative of expressions of the users in the images. A live image of a user is captured using an eye tracking sensor implemented in an HMD worn by the user. A label of an expression evinced by the user in the live image is inferred using the machine learnt algorithm that has been trained to predict labels indicative of expressions. The images of the users and the live image can be personalized by combining the images with personalization images of the users evincing a subset of the expressions.

公开(公告)号：US20230040793A1

公开(公告)日：2023-02-09

申请号：US17870462

申请日：2022-07-21

Applicant: Google LLC

Inventor： Avneesh Sud ,  Andrea Tagliasacchi ,  Ben Usman

IPC: G06V10/77 ,  G06N5/02 ,  G06T7/70

Abstract: Example systems perform complex optimization tasks with improved efficiency via neural meta-optimization of experts. In particular, provided is a machine learning framework in which a meta-optimization neural network can learn to fuse a collection of experts to provide a predicted solution. Specifically, the meta-optimization neural network can learn to predict the output of a complex optimization process which optimizes over outputs from the collection of experts to produce an optimized output. In such fashion, the meta-optimization neural network can, after training, be used in place of the complex optimization process to produce a synthesized solution from the experts, leading to orders of magnitude faster and computationally more efficient prediction or problem solution.