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:
Dec. 24, 2024

Filed:

Mar. 11, 2022
Applicant:

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

Inventors:

Vitor Guizilini, Santa Clara, CA (US);

Adrien David Gaidon, Mountain View, CA (US);

Rares A. Ambrus, San Francisco, CA (US);

Igor Vasiljevic, Fort Lauderdale, FL (US);

Jiading Fang, Chicago, IL (US);

Gregory Shakhnarovich, Chicago, IL (US);

Matthew R. Walter, Chicago, IL (US);

Assignees:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 3/18 (2024.01); G06T 5/80 (2024.01); G06T 7/50 (2017.01); G06T 7/80 (2017.01); B60W 60/00 (2020.01); B64C 39/02 (2023.01); G05D 1/00 (2006.01); H04N 17/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/80 (2017.01); G06T 3/18 (2024.01); G06T 5/80 (2024.01); G06T 7/50 (2017.01); B60W 60/001 (2020.02); B60W 2420/403 (2013.01); B64C 39/024 (2013.01); B64U 2201/00 (2023.01); G05D 1/0246 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30244 (2013.01); G06T 2207/30252 (2013.01); H04N 17/002 (2013.01);
Abstract

Systems and methods described herein relate to self-supervised learning of camera intrinsic parameters from a sequence of images. One embodiment produces a depth map from a current image frame captured by a camera; generates a point cloud from the depth map using a differentiable unprojection operation; produces a camera pose estimate from the current image frame and a context image frame; produces a warped point cloud based on the camera pose estimate; generates a warped image frame from the warped point cloud using a differentiable projection operation; compares the warped image frame with the context image frame to produce a self-supervised photometric loss; updates a set of estimated camera intrinsic parameters on a per-image-sequence basis using one or more gradients from the self-supervised photometric loss; and generates, based on a converged set of learned camera intrinsic parameters, a rectified image frame from an image frame captured by the camera.


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