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. 28, 2021

Filed:

Jan. 23, 2018
Applicant:

Intelligent Fusion Technology, Inc, Germantown, MD (US);

Inventors:

Dan Shen, Germantown, MD (US);

Peter Zulch, Rome, NY (US);

Marcello Disasio, Rome, NY (US);

Erik Blasch, Arlington, VA (US);

Genshe Chen, Germantown, MD (US);

Zhonghai Wang, Germantown, MD (US);

Jingyang Lu, Germantown, MD (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06N 7/08 (2006.01); G06K 9/68 (2006.01); G06T 7/80 (2017.01); H04N 5/33 (2006.01); G01S 13/58 (2006.01); G06K 9/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6288 (2013.01); G01S 13/58 (2013.01); G06K 9/0063 (2013.01); G06K 9/6248 (2013.01); G06K 9/685 (2013.01); G06N 7/08 (2013.01); G06T 7/80 (2017.01); H04N 5/33 (2013.01); G06K 2009/6871 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30252 (2013.01);
Abstract

The present disclosure provides a method for joint manifold learning based heterogenous sensor data fusion, comprising: obtaining learning heterogeneous sensor data from a plurality sensors to form a joint manifold, wherein the plurality sensors include different types of sensors that detect different characteristics of targeting objects; performing, using a hardware processor, a plurality of manifold learning algorithms to process the joint manifold to obtain raw manifold learning results, wherein a dimension of the manifold learning results is less than a dimension of the joint manifold; processing the raw manifold learning results to obtain intrinsic parameters of the targeting objects; evaluating the multiple manifold learning algorithms based on the raw manifold learning results and the intrinsic parameters to determine one or more optimum manifold learning algorithms; and applying the one or more optimum manifold learning algorithms to fuse heterogeneous sensor data generated by the plurality sensors.


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