Invention Grant
- Patent Title: Machine learning models for implementing animation actions
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Application No.: US16125288Application Date: 2018-09-07
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Publication No.: US10765944B2Publication Date: 2020-09-08
- Inventor: Cesar Dantas de Castro
- Applicant: Electronic Arts, Inc.
- Applicant Address: US CA Redwood City
- Assignee: Electronic Arts Inc.
- Current Assignee: Electronic Arts Inc.
- Current Assignee Address: US CA Redwood City
- Agency: Lee & Hayes, P.C.
- Main IPC: A63F9/00
- IPC: A63F9/00 ; A63F13/52 ; G06T7/70 ; G06T7/20 ; G06T13/40 ; G06K9/00

Abstract:
An animation system and method generates predictive models that are deployed in animations, such as an animation associated with a video game, to predict outcomes resulting from events occurring in the animation, such as interactions between two or more objects in the animation. These predictive models may be generated based at least in part on training data that is generated by running the animation, such as playing a video game, generating parameter values associated with events in the animation, and determining an outcome of the events. The training data may be used to generate predictive models, such as by using machine learning algorithms. The predictive models may then be deployed in the animation, such as in a video game, to make real time or near real-time predictions of outcomes based at least in part on events in the animation.
Public/Granted literature
- US20200078679A1 MACHINE LEARNING MODELS FOR IMPLEMENTING ANIMATION ACTIONS Public/Granted day:2020-03-12
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