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. 22, 2020

Filed:

Jun. 25, 2018
Applicant:

Affectiva, Inc., Boston, MA (US);

Inventors:

Jason Krupat, Needham, MA (US);

Rana el Kaliouby, Milton, MA (US);

Jason Radice, Sharon, NH (US);

Chilton Lyons Cabot, Dedham, MA (US);

Assignee:

Affectiva, Inc., Boston, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/16 (2006.01); G06Q 30/02 (2012.01); G16H 50/20 (2018.01); G16H 30/40 (2018.01); G06Q 50/00 (2012.01); G06F 19/00 (2018.01); A61B 5/00 (2006.01); A61B 5/18 (2006.01); A61B 5/1171 (2016.01); A61B 5/01 (2006.01); G16H 40/67 (2018.01); G06Q 10/10 (2012.01); A61B 3/113 (2006.01); A61B 5/08 (2006.01); A61B 5/024 (2006.01); A61B 5/0205 (2006.01); A61B 5/11 (2006.01); A61B 5/053 (2006.01);
U.S. Cl.
CPC ...
A61B 5/165 (2013.01); A61B 5/0077 (2013.01); A61B 5/015 (2013.01); A61B 5/1176 (2013.01); A61B 5/18 (2013.01); A61B 5/4833 (2013.01); A61B 5/4842 (2013.01); A61B 5/7264 (2013.01); A61B 5/7275 (2013.01); G06F 19/3418 (2013.01); G06F 19/3481 (2013.01); G06Q 10/10 (2013.01); G06Q 30/0201 (2013.01); G06Q 30/0271 (2013.01); G06Q 30/0282 (2013.01); G06Q 50/01 (2013.01); G16H 30/40 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); A61B 3/113 (2013.01); A61B 5/02055 (2013.01); A61B 5/02405 (2013.01); A61B 5/0533 (2013.01); A61B 5/08 (2013.01); A61B 5/11 (2013.01); A61B 5/6824 (2013.01);
Abstract

Techniques are described for image analysis and representation for emotional metric threshold generation. A client device is used to collect image data of a user interacting with a media presentation, where the image data includes facial images of the user. One or more processors are used to analyze the image data to extract emotional content of the facial images. One or more emotional intensity metrics are determined based on the emotional content. The one or more emotional intensity metrics are stored into a digital storage component. The one or more emotional intensity metrics, obtained from the digital storage component, are coalesced into a summary emotional intensity metric. The summary emotional intensity metric is represented.


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