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:
Aug. 27, 2024

Filed:

Apr. 22, 2022
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Boris Cherevatsky, Modiin, IL;

Roman Goldenberg, Haifa, IL;

Gerard Guy Medioni, Los Angeles, CA (US);

Ofer Meidan, Hadera, IL;

Ehud Benyamin Rivlin, Haifa, IL;

Dilip Kumar, Seattle, WA (US);

Assignee:

Amazon Technologies, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/292 (2017.01); G06F 18/2113 (2023.01); G06F 18/2415 (2023.01); G06T 7/55 (2017.01); G06T 11/60 (2006.01); H04N 7/18 (2006.01); H04N 23/90 (2023.01);
U.S. Cl.
CPC ...
G06T 7/292 (2017.01); G06F 18/2113 (2023.01); G06F 18/2415 (2023.01); G06T 7/55 (2017.01); G06T 11/60 (2013.01); H04N 7/181 (2013.01); H04N 7/188 (2013.01); H04N 23/90 (2023.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2210/12 (2013.01);
Abstract

The motion of objects within a scene may be detected and tracked using digital (e.g., visual and depth) cameras aligned with fields of view that overlap at least in part. Objects may be identified within visual images captured from the scene using a tracking algorithm and correlated to point clouds or other depth models generated based on depth images captured from the scene. Once visual aspects (e.g., colors or other features) of objects are correlated to the point clouds, shapes and/or positions of the objects may be determined and used to further train the tracking algorithms to recognize the objects in subsequently captured frames. Moreover, a Kalman filter or other motion modeling technique may be used to enhance the prediction of a location of an object within subsequently captured frames.


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