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. 26, 2025

Filed:

Jan. 06, 2022
Applicant:

Nvidia Corporation, Santa Clara, CA (US);

Inventors:

Yang Fu, Urbana, IL (US);

Sifei Liu, Santa Clara, CA (US);

Umar Iqbal, San Jose, CA (US);

Shalini De Mello, San Francisco, CA (US);

Jan Kautz, Lexington, MA (US);

Assignee:

NVIDIA Corporation, Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06T 7/248 (2017.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A method and system are provided for tracking instances within a sequence of video frames. The method includes the steps of processing an image frame by a backbone network to generate a set of feature maps, processing the set of feature maps by one or more prediction heads, and analyzing the embedding features corresponding to a set of instances in two or more image frames of the sequence of video frames to establish a one-to-one correlation between instances in different image frames. The one or more prediction heads includes an embedding head configured to generate a set of embedding features corresponding to one or more instances of an object identified in the image frame. The method may also include training the one or more prediction heads using a set of annotated image frames and/or a plurality of sequences of unlabeled video frames.


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