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.:

US 10867165 B1

Date of Patent:

Dec. 15, 2020

Filed:

Jan. 31, 2019

Custom gesture collection and recognition system having machine learning accelerator

Applicant:

Kaikutek Inc., Taipei, TW;

Inventor:

Mike Chun Hung Wang, Taipei, TW;

Assignee:

KaiKuTek INC., Taipei, TW;

Attorney:

Winston Hsu

Primary Examiner:

Hugo Molina

Int. Cl.

CPC ...

G06F 3/01 (2006.01); G01S 7/41 (2006.01); G01S 13/02 (2006.01); H04W 72/00 (2009.01); G06N 20/00 (2019.01); G06K 9/00 (2006.01); G06K 9/62 (2006.01); G01S 13/89 (2006.01); G06K 9/20 (2006.01); G06K 9/46 (2006.01); G06F 9/50 (2006.01); G06N 3/08 (2006.01); H03B 21/02 (2006.01); G01S 13/58 (2006.01); G06T 7/20 (2017.01); G06F 17/18 (2006.01); G01S 13/50 (2006.01); G01S 7/35 (2006.01);

U.S. Cl.

CPC ...

G06K 9/00335 (2013.01); G01S 7/414 (2013.01); G01S 7/417 (2013.01); G01S 13/584 (2013.01); G01S 13/89 (2013.01); G06F 3/017 (2013.01); G06F 9/5027 (2013.01); G06F 17/18 (2013.01); G06K 9/2018 (2013.01); G06K 9/4628 (2013.01); G06K 9/6215 (2013.01); G06K 9/6256 (2013.01); G06K 9/6259 (2013.01); G06K 9/6262 (2013.01); G06K 9/6267 (2013.01); G06K 9/6271 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06T 7/20 (2013.01); H03B 21/02 (2013.01); G01S 7/415 (2013.01); G01S 13/50 (2013.01); G01S 2007/356 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);

Abstract

A gesture recognition system includes a transmission unit, a first reception chain, a second reception chain, a customized gesture collection engine and a machine learning accelerator. The transmission unit is used to transmit a transmission signal to detect a gesture. The first reception chain is used to receive a first signal and generate first feature map data corresponding to the first signal. The second reception chain is used to receive a second signal and generate second feature map data corresponding to the second signal. The first signal and the second signal are generated by the gesture reflecting the transmission signal. The customized gesture collection engine is used to generate gesture data according to at least the first feature map data and the second feature map data. The machine learning accelerator is used to perform machine learning with the gesture data.

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