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.
Patent No.:
Date of Patent:
Aug. 20, 2024
Filed:
Nov. 11, 2020
Google Llc, Mountain View, CA (US);
Sean Ryan Francesco Fanello, San Francisco, CA (US);
Kaiwen Guo, Beijing, CN;
Peter Christopher Lincoln, San Francisco, CA (US);
Philip Lindsley Davidson, Arlington, MA (US);
Jessica L. Busch, Long Beach, CA (US);
Xueming Yu, Arcadia, CA (US);
Geoffrey Harvey, Culver City, CA (US);
Sergio Orts Escolano, San Francisco, CA (US);
Rohit Kumar Pandey, Mountain View, CA (US);
Jason Dourgarian, Los Angeles, CA (US);
Danhang Tang, San Francisco, CA (US);
Adarsh Prakash Murthy Kowdle, San Francisco, CA (US);
Emily B. Cooper, San Francisco, CA (US);
Mingsong Dou, Cupertino, CA (US);
Graham Fyffe, Los Angeles, CA (US);
Christoph Rhemann, Marina Del Rey, CA (US);
Jonathan James Taylor, San Francisco, CA (US);
Shahram Izadi, Tiburon, CA (US);
Paul Ernest Debevec, Culver City, CA (US);
GOOGLE LLC, Mountain View, CA (US);
Abstract
A lighting stage includes a plurality of lights that project alternating spherical color gradient illumination patterns onto an object or human performer at a predetermined frequency. The lighting stage also includes a plurality of cameras that capture images of an object or human performer corresponding to the alternating spherical color gradient illumination patterns. The lighting stage also includes a plurality of depth sensors that capture depth maps of the object or human performer at the predetermined frequency. The lighting stage also includes (or is associated with) one or more processors that implement a machine learning algorithm to produce a three-dimensional (3D) model of the object or human performer. The 3D model includes relighting parameters used to relight the 3D model under different lighting conditions.