IP Library › Granted Patent US 12,403,400
Granted Patent B2
US 12,403,400 · App. 17/657,591 · Granted Sep 2, 2025

Learning character motion alignment with periodic autoencoders

Inventors: Wolfram Sebastian Starke (Edinburgh, GB); Harold Henry Chaput (Castro Valley, CA)
Assignee: Electronic Arts Inc.
A63F13/57G06T13/40G06T13/80
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Quick Facts
Patent No.
US 12,403,400
App. No.
17/657,591
Granted
Sep 2, 2025
Kind
B2
Abstract

The present disclosure provides a periodic autoencoder that can be used to generate a general motion manifold structure using local periodicity of the movement whose parameters are composed of phase, frequency, and amplitude. The periodic autoencoder is a novel neural network architecture that can learn periodic features from large unstructured motion datasets in an unsupervised manner. The character movements can be decomposed into multiple latent channels that can capture the non-linear periodicity of different body segments during synchronous, asynchronous, and transition movements while progressing forward in time, such that it captures spatial data and temporal data associated with the movements.

Claims (39)

1. A computer-implemented method comprising:

as implemented by a computing system having at least one processor configured with specific computer-executable instructions,

accessing first animation control information generated for a first frame of an electronic game, the first animation control information including a first pose of an in-game character model;

executing a motion matching process using a motion phase manifold comprising a plurality of local motion phase channels, wherein each local motion phase channel comprises spatial and temporal data for movement of a segment of the in-game character model, the motion matching process results in a plurality of matched local poses, the motion matching process comprising:

determining motion matching criteria for matching the local motion phase to existing local poses within a local pose animation dataset for the corresponding local motion phase channel;

performing a search of the local motion phase channel to identify a plurality of local poses within the local pose animation dataset based on the motion matching criteria;

calculating a score for the plurality of local poses based on reference features associated with the local motion phase; and

selecting a local pose from the plurality of local poses corresponding to the local motion phase based on the score;

generating a second pose of the in-game character model based on the plurality of matched local poses for a second frame of the electronic game;

computing second animation control information for the second frame; and

rendering the second frame including at least a portion of the second pose of the in-game character model within an in-game environment based, at least in part, on the second animation control information.

2. The computer-implemented method of claim 1 , wherein a plurality of local motion phase channels are associated with the in-game character model of the electronic game and individual local motion phase channels represent phase information associated with the first pose of the in-game character model within the in-game environment.

3. The computer-implemented method of claim 2 , wherein the local motion phase channel is represented by a two dimensional vector encoded with the reference features of the local motion phase.

4. The computer-implemented method of claim 3 , wherein the reference features include phase, frequency, and amplitude.

5. The computer-implemented method of claim 3 , wherein performing the search comprises performing a nearest neighbor search using the two dimensional vector of the local motion phase channel as compared to two dimensional vectors of local poses in the animation data.

6. The computer-implemented method of claim 1 , wherein determining motion matching criteria comprises identifying a motion type associated with the second pose of the in-game character model.

7. The computer-implemented method of claim 6 , wherein determining motion matching criteria comprises identifying a subset of the animation data corresponding to the motion type.

8. The computer-implemented method of claim 1 , wherein generating the second pose of the in-game character model comprises blending the plurality of local poses with a global pose to generate the second pose.

9. The computer-implemented method of claim 1 , wherein the first animation control information comprises information aggregated over a prior threshold number of frames.

10. The computer-implemented method of claim 1 , wherein the second animation control information includes updated local motion phase channels, and wherein the updated local motion phase channels are determined via interpolation of the local motion phase channels included in the first animation control information.

11. A system comprising one or more processors and non-transitory computer storage media storing computer-readable instructions that when executed by the one or more processors, cause the one or more processors to perform operations comprising:

accessing first animation control information generated for a first frame of an electronic game, the first animation control information including a first pose of an in-game character model;

executing a motion matching process using a motion phase manifold comprising a plurality of local motion phase channels, wherein each local motion phase channel comprises spatial and temporal data for movement of a segment of the in-game character model, the motion matching process results in a plurality of matched local poses, the motion matching process comprising:

determining motion matching criteria for matching the local motion phase to existing local poses within a local pose animation dataset for the corresponding local motion phase channel;

performing a search of the local motion phase channel to identify a plurality of local poses within the local pose animation dataset based on the motion matching criteria;

calculating a score for the plurality of local poses based on reference features associated with the local motion phase; and

selecting a local pose from the plurality of local poses corresponding to the local motion phase based on the score;

generating a second pose of the in-game character model based on the plurality of matched local poses for a second frame of the electronic game;

computing second animation control information for the second frame; and

rendering the second frame including at least a portion of the second pose of the in-game character model within an in-game environment based, at least in part, on the second animation control information.

12. The system of claim 11 , wherein a plurality of local motion phase channels are associated with the in-game character of the electronic game, individual local motion phase channels representing phase information associated with contacts of at least one rigid body of the in-game character model with the in-game environment.

13. The system of claim 12 , wherein the local motion phase channel is represented by a two dimensional vector encoded with the reference features of the local motion phase.

14. The system of claim 13 , wherein the reference features include position, orientation, velocity, and acceleration.

15. The system of claim 13 , wherein the computer-readable instructions further configure the one or more processors to perform a nearest neighbor search using the two dimensional vector of the local motion phase as compared to two dimensional vectors of local poses in the animation data when performing the search.

16. The system of claim 11 , wherein the computer-readable instructions further configure the one or more processors to identify a motion type associated with the second pose of the in-game character model when determining motion matching criteria.

17. The system of claim 16 , wherein the computer-readable instructions further configure the one or more processors to identify a subset of the animation data corresponding to the motion type when determining motion matching criteria.

18. The system of claim 11 , wherein the computer-readable instructions further configure the one or more processors to blend the plurality of local poses with a global pose to generate the second pose when generating the second pose of the in-game character model.

19. The system of claim 11 , wherein the local motion phase channels further represent phase information associated with an external object configured to be interacted with by the in-game character model.

20. The system of claim 11 , wherein the second animation control information includes updated local motion phase channels, and wherein the updated local motion phase channels are determined via interpolation of the local motion phase channels included in the first animation control information.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 13, 2022
From: STARKE, WOLFRAM SEBASTIAN
To: ELECTRONIC ARTS INC.
Reel/Frame 061082/0746 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 13, 2022
From: CHAPUT, HAROLD HENRY
To: ELECTRONIC ARTS INC.
Reel/Frame 061082/0764 →
Continuity (1)
Related Publication 20230310998A1 · Oct 5, 2023
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