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. 10, 2024

Filed:

Nov. 15, 2019
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Chloe LeGendre, Culver City, CA (US);

Wan-Chun Ma, Culver City, CA (US);

Graham Fyffe, Los Angeles, CA (US);

John Flynn, Los Angeles, CA (US);

Jessica Busch, Gardena, CA (US);

Paul Debevec, Culver City, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/60 (2022.01); G06V 10/44 (2022.01); G06V 10/75 (2022.01); G06V 20/40 (2022.01);
U.S. Cl.
CPC ...
G06V 10/60 (2022.01); G06V 10/443 (2022.01); G06V 10/751 (2022.01); G06V 20/46 (2022.01);
Abstract

An example method, apparatus, and computer-readable storage medium are provided to predict high-dynamic range (HDR) lighting from low-dynamic range (LDR) background images. In an example implementation, a method may include receiving low-dynamic range (LDR) background images of scenes, each LDR background image captured with appearance of one or more reference objects with different reflectance properties; and training a lighting estimation model based at least on the received LDR background images to predict high-dynamic range (HDR) lighting based at least on the trained model. In another example implementation, a method may include capturing a low-dynamic range (LDR) background image of a scene from an LDR video captured by a camera of the electronic computing device; predicting high-dynamic range (HDR) lighting for the image, the predicting, using a trained model, based at least on the LDR background image; and rendering a virtual object based at least on the predicted HDR lighting.


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