Systems and methods for animating non-humanoid characters with human motion data

1. A method for animation comprising:

selecting key poses included in initial motion data at a computing system;

obtaining non-humanoid character key poses which provide a one to one correspondence to selected key poses in said initial motion data; and

statically mapping poses of said initial motion data to non-humanoid character poses using a model built based on said one to one correspondence from said key poses of said initial motion data to said non-humanoid character key poses,

wherein said statically mapping further comprises learning a static mapping function from poses of said initial motion data to said non-humanoid character poses, and

wherein said model is a shared Gaussian process latent variable model.

2. The method according to claim 1 , further comprising optimizing statically mapped data for a non-humanoid character to create a physically correct animated motion for said non-humanoid character.

3. The method according to claim 1 , wherein said initial motion data is derived from one or more of: a motion capture system, and a key framing process.

4. The method according to claim 3 , wherein the initial motion data is human motion capture data.

5. The method according to claim 1 , wherein said selecting key poses included in said initial motion data is performed by a user operating an animation system.

6. The method according to claim 1 , wherein said non-humanoid character key poses are derived from an external device.

7. The method according to claim 1 , wherein said non-humanoid character key poses comprise key poses created by an animator collaborating with one or more actors.

8. The method according to claim 2 , wherein said optimizing statically mapped data for a non-humanoid character further comprises one or more of:

determining a global transformation of said non-humanoid character poses;

correcting one or more contact positions; and

optimizing physical realism of non-humanoid character motion by adjusting vertical motion to be consistent with gravity and a penalty-based contact model.

9. A computer program product comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising:

computer readable program code configured to access key poses selected from initial motion data;

computer readable program code configured to access non-humanoid character key poses which provide a one to one correspondence to selected key poses in said initial motion data; and

computer readable program code configured to statically map poses of said initial motion data to non-humanoid character poses using a model built based on said one to one correspondence from said key poses of said initial motion data to said non-humanoid character key poses,

wherein said mapping further comprises learning a static mapping function from poses of said initial motion data to said non-humanoid character poses, and

wherein said model is a shared Gaussian process latent variable model.

10. The computer program product according to claim 9 , further comprising computer readable program code configured to optimize statically mapped data for a non-humanoid character to create a physically correct animated motion for said non-humanoid character.

11. The computer program product according to claim 9 , wherein said initial motion data is derived from one or more of: a motion capture system, and a key framing process.

12. The computer program product according to claim 10 , wherein the initial motion data is human motion capture data.

13. The computer program product according to claim 10 , wherein said optimizing statically mapped data for a non-humanoid character further comprises one or more of:

determining a global transformation of said non-humanoid character poses;

correcting one or more contact positions; and

optimizing physical realism of non-humanoid character motion by adjusting motion of said non-humanoid character to be consistent with gravity and a penalty-based contact model.

14. The computer program product according to claim 13 , further comprising computer readable program code configured to match linear and angular momenta of said non-humanoid character poses to poses obtained by scaling momenta in poses of said initial input data.

15. The computer program product according to claim 13 , wherein said optimizing physical realism of said non-humanoid character motion further comprises adjusting vertical motion of said non-humanoid character.

16. A system comprising:

at least one processor; and

a memory device operatively connected to the at least one processor;

wherein, responsive to execution of program instructions accessible to the at least one processor, the at least one processor is configured to:

access key poses selected from initial motion data;

access non-humanoid character key poses which provide a one to one correspondence to selected key poses in said initial motion data; and

statically map poses of said initial motion data to non-humanoid character poses using a model built based on said one to one correspondence from said key poses of said initial motion data to said non-humanoid character key poses,

wherein said mapping further comprises learning a static mapping function from poses of said initial motion data to said non-humanoid character poses, and

wherein said model is a shared Gaussian process latent variable model.