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:
Sep. 24, 2024

Filed:

May. 27, 2021
Applicant:

Stats Llc, Chicago, IL (US);

Inventors:

Xinyu Wei, Melbourne, AU;

Jennifer Hobbs, Chicago, IL (US);

Long Sha, Brisbane, AU;

Patrick Joseph Lucey, Chicago, IL (US);

Sujoy Ganguly, Chicago, IL (US);

Assignee:

Stats LLC, Chicago, IL (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06K 9/62 (2022.01); G06N 3/04 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06V 10/82 (2022.01); G06V 20/40 (2022.01); G06V 20/52 (2022.01); G06V 40/20 (2022.01);
U.S. Cl.
CPC ...
G06V 40/20 (2022.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/82 (2022.01); G06V 20/42 (2022.01); G06V 20/46 (2022.01); G06V 20/52 (2022.01);
Abstract

A method and system of generating agent and actions prediction based on multi-agent tracking data are disclosed herein. A computing system retrieves tracking data from a data store. The computing system generates a trained neural network by generating a plurality of training data sets based on the tracking data by converting each frame of data into a matrix representation of the data contained in the frame and learning, by the neural network, a start frame and end frame of each action contained in the frame and its associated actor. The computing system receives target tracking data associated with an event. The target tracking data includes a plurality of actors and a plurality of actions. The computing system generates, via the trained neural network, a target start frame and a target end frame of each action identified in the tracking data and a corresponding actor.


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