The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 11, 2022

Filed:

Jan. 16, 2020
Applicants:

Toyota Research Institute, Inc., Los Altos, CA (US);

Massachusetts Institute of Technology, Cambridge, MA (US);

Inventors:

Simon A. I. Stent, Cambridge, MA (US);

Adrià Recasens, Cambridge, MA (US);

Petr Kellnhofer, Cambridge, MA (US);

Wojciech Matusik, Cambridge, MA (US);

Antonio Torralba, Cambridge, MA (US);

Assignees:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 3/00 (2006.01); G06F 3/01 (2006.01); G06N 3/08 (2006.01); G06T 7/73 (2017.01); G02B 27/00 (2006.01);
U.S. Cl.
CPC ...
G06F 3/013 (2013.01); G02B 27/0093 (2013.01); G06N 3/08 (2013.01); G06T 7/73 (2017.01); G06T 2207/30041 (2013.01); G06T 2207/30201 (2013.01);
Abstract

A system includes a camera positioned in an environment to capture image data of a subject; a computing device communicatively coupled to the camera, the computing device comprising a processor and a non-transitory computer-readable memory; and a machine-readable instruction set stored in the non-transitory computer-readable memory. The machine-readable instruction set causes the computing device to perform at least the following when executed by the processor: receive the image data from the camera; analyze the image data captured by the camera using a neural network trained on training data generated from a 360-degree panoramic camera configured to collect image data of a subject and a visual target that is moved about an environment; and predict a gaze direction vector of the subject with the neural network.


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