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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 11657650 B1

PDFFull Text
Date of Patent:
May. 23, 2023

Filed:

Jan. 15, 2021

Techniques for automatically identifying secondary objects in a stereo-optical counting system

Applicant:

Sensormatic Electronics, Llc, Boca Raton, FL (US);

Inventors:

Zhiqian Wang, Lisle, IL (US);

Edward A. Marcheselli, Wheaton, IL (US);

Gary Dispensa, Naperville, IL (US);

Thomas D. Stemen, Naperville, IL (US);

William C. Kastilahn, Evanston, IL (US);

Assignee:

Sensormatic Electronics, LLC, Boca Raton, FL (US);

Attorney:

ArentFox Schiff LLP

Primary Examiner:

Andrew W Johns

Int. Cl.
CPC ...
G06T 7/73 (2017.01); G06T 7/11 (2017.01); G06V 20/52 (2022.01); G06V 40/20 (2022.01); G06T 7/20 (2017.01); G07C 9/00 (2020.01); G06F 16/58 (2019.01); G06F 16/55 (2019.01); G06T 7/187 (2017.01); G07C 9/28 (2020.01);
U.S. Cl.
CPC ...
G06V 40/20 (2022.01); G06F 16/55 (2019.01); G06F 16/5866 (2019.01); G06T 7/11 (2017.01); G06T 7/187 (2017.01); G06T 7/20 (2013.01); G06T 7/73 (2017.01); G06V 20/53 (2022.01); G06V 40/23 (2022.01); G07C 9/00 (2013.01); G07C 9/00896 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30232 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30242 (2013.01); G07C 9/00904 (2013.01); G07C 9/28 (2020.01); G07C 2209/08 (2013.01); G07C 2209/64 (2013.01);
Abstract

Techniques for distinguishing objects (e.g., an individual or an individual pushing a shopping cart) are disclosed. An object is detected in images of a scene. A height map is generated from the images, and the object is represented as height values in the height map. Based on height properties associated with another object, it is determined whether the other object is associated with the object. If so determined, the objects are classified separately.

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