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:
Sep. 24, 2019

Filed:

Oct. 21, 2015
Applicant:

Lg Electronics Inc., Seoul, KR;

Inventors:

Amir Said, San Jose, CA (US);

Yung-Hsuan Chao, San Jose, CA (US);

Hilmi Enes Egilmez, San Jose, CA (US);

Assignee:

LG Electronics Inc., Seoul, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/19 (2014.01); H04N 19/159 (2014.01); A45F 5/00 (2006.01); A45C 11/00 (2006.01); A45C 13/10 (2006.01); H04N 19/105 (2014.01); H04N 19/18 (2014.01); H04N 19/44 (2014.01); H04N 19/503 (2014.01); H04N 19/61 (2014.01); H04N 19/50 (2014.01); H04N 19/103 (2014.01); H04N 19/136 (2014.01);
U.S. Cl.
CPC ...
H04N 19/159 (2014.11); A45C 11/00 (2013.01); A45C 13/1069 (2013.01); A45F 5/00 (2013.01); H04N 19/103 (2014.11); H04N 19/105 (2014.11); H04N 19/136 (2014.11); H04N 19/18 (2014.11); H04N 19/19 (2014.11); H04N 19/44 (2014.11); H04N 19/50 (2014.11); H04N 19/503 (2014.11); H04N 19/61 (2014.11); A45C 2011/002 (2013.01); A45F 2005/008 (2013.01); A45F 2200/0516 (2013.01);
Abstract

Performing a graph-based prediction using a graph signal can be performed using a method that includes obtaining a context signal; generating a graph signal based on a graph parameter set; obtaining a graph-based transform matrix based on the graph signal, wherein the graph-based transform matrix includes an eigenvector; obtaining a prediction vector using an optimal transform vector calculated through an optimization function; and generating a prediction signal using the prediction vector, where the optimization function has the context signal, an eigenvalue of a graph Laplacian matrix and the eigenvector as a variable. Accordingly, a prediction value may be obtained with reduced complexity and the prediction performance may be improved.


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