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:
Jan. 04, 2022

Filed:

Jan. 19, 2017
Applicant:

Coral Detection Systems Ltd., Zichron Yaacov, IL;

Inventors:

Eyal Golan, Zichron Yaacov, IL;

Tamar Avraham, Haifa, IL;

Assignee:

CORAL DETECTION SYSTEMS LTD., Zichron Yaacov, IL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G08B 21/08 (2006.01); G06K 9/46 (2006.01); G06K 9/62 (2006.01); G06T 7/73 (2017.01); G06N 3/08 (2006.01); G06T 7/00 (2017.01); G06T 7/20 (2017.01); H04N 7/18 (2006.01); G08B 29/18 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00335 (2013.01); G06K 9/00771 (2013.01); G06K 9/4628 (2013.01); G06K 9/6271 (2013.01); G06N 3/08 (2013.01); G06T 7/0002 (2013.01); G06T 7/20 (2013.01); G06T 7/73 (2017.01); G08B 21/08 (2013.01); H04N 7/185 (2013.01); G08B 21/084 (2013.01); G08B 29/188 (2013.01);
Abstract

It is provided a method of detecting human drowning, comprising: attempting to detect humans in a sequence of underwater images taken by a single camera, for identifying humans-in-water candidates in the images, said detection using at least a machine learning algorithm, tracking humans-in-water candidates throughout this sequence, and detecting human drowning risk. It is also provided a system for detecting human drowning, comprising at least one underwater camera configured to take at least a sequence of underwater images, the system being configured to attempt to detect humans in the sequence of underwater images, for identifying humans-in-water candidates in the images, said detection using at least a machine learning algorithm, track humans-in-water candidates throughout this sequence, and detect human drowning risk.


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