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:
Jul. 28, 2020

Filed:

Feb. 01, 2018
Applicant:

Ford Global Technologies, Llc, Dearborn, MI (US);

Inventors:

Venkatapathi Raju Nallapa, Fairfield, CA (US);

Anjali Krishnamachar, Mountain View, CA (US);

Gautham Sholingar, Sunnyvale, CA (US);

Assignee:

FORD GLOBAL TECHNOLOGIES, LLC, Dearborn, MI (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G05D 1/02 (2020.01);
U.S. Cl.
CPC ...
G06K 9/00335 (2013.01); G05D 1/0231 (2013.01); G05D 1/0257 (2013.01);
Abstract

The present invention extends to methods, systems, and computer program products for validating gesture recognition capabilities of automated systems. Aspects include a gesture recognition training system that is scalable, efficient, repeatable, and accounts for permutations of physical characteristics, clothing, types of gestures, environment, culture, weather, road conditions, etc. The gesture recognition training system includes sensors and algorithms used to generate training data sets that facilitate more accurate recognition of and reaction to human gestures. A training data set can be scaled from both monitoring and recording gestures performed by a humanoid robot and performed by animated humans in a simulation environment. From a scaled training data set, autonomous devices can be trained to recognize and react to a diverse set of human gestures in varying conditions with substantially improved capabilities. Recognition capabilities of an autonomous device can be validated and (re)trained until recognition capabilities are determined to be sufficient.


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