IP Library › Granted Patent US 11,004,248
Granted Patent B2
US 11,004,248 · App. 17/087,503 · Granted May 11, 2021

Apparatus and method for performing motion capture using a random pattern on capture surfaces

Inventors: Timothy Cotter (Sunnyvale, CA); Stephen G. Perlman (Palo Alto, CA); John Speck (Brainbridge Island, WA); Roger van der Laan (Redwood City, CA); Kenneth A. Pearce (San Francisco, CA); Greg LaSalle (Culver City, CA)
Assignee: Rearden Mova, LLC
G06T13/40G06K9/3216G06T7/20G06T7/246G06T7/292H04N5/2224H04N5/2256H04N5/2353H04N5/2354H04N5/247H04N13/239H04N13/243G06K2009/3225G06T2207/10016G06T2207/30196
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Quick Facts
Patent No.
US 11,004,248
App. No.
17/087,503
Granted
May 11, 2021
Kind
B2
Abstract

A method is described comprising: applying a random pattern to specified regions of an object; tracking the movement of the random pattern during a motion capture session; and generating motion data representing the movement of the object using the tracked movement of the random pattern.

Claims (52)

1. A system comprising:

a plurality of cameras, each capturing a plurality of two-dimensional (2D) frames of some or all of a surface of a performer's face as the performer's face changes in some or all of the plurality of time intervals;

a processor that correlates the plurality of 2D frames from the plurality of cameras at the plurality of time intervals to create a high-resolution three-dimensional (3D) mesh corresponding to a 3D shape of some or all of the surface of the performer's face at some or all of the time intervals;

wherein a first plurality of 3D points in the high-resolution 3D mesh automatically track a second plurality of 3D points on the surface of the performer's face;

wherein the second plurality of 3D points on the surface of the performer's face are not identified by markers applied to the performer's face.

2. The system of claim 1 wherein the first plurality of 3D points automatically track the second plurality of 3D points within regions of the performer's face that fold or deform.

3. The system of claim 1 wherein the first plurality of 3D points automatically track the second plurality of 3D points that include some or all parts of the eyes, lips, or teeth.

4. The system of claim 1 wherein the 3D mesh for one or more time intervals corresponds to a facial expressions.

5. The system of claim 1 wherein the surface of the performer's face in visible light is captured by the same plurality of cameras or one or more different cameras.

6. The system of claim 1 wherein the time intervals are successive frame times.

7. The system of claim 1 wherein at least some of the time intervals are not successive frame times.

8. The system of claim 1 wherein the processor correlates the 2D frames at a first resolution, and then correlates the 2D frames at a second resolution that is a higher resolution than the first resolution.

9. A method comprising:

correlating 2D frames from a plurality of cameras at a plurality of time intervals, each camera capturing a plurality of 2D frames of some or all of a surface of a performer's face as the performer's face changes in some or all of the plurality of time intervals;

creating a high-resolution three-dimensional (3D) mesh corresponding to a 3D shape of the surface of some or all of the performer's face at some or all of the time intervals;

a first plurality of 3D points in the high-resolution 3D mesh automatically tracking a second plurality of 3D points on the surface of the performer's face;

wherein the second plurality of 3D points on the surface of the performer's face are not identified by markers applied to the performer's face.

10. The method of claim 9 further comprising:

the first plurality of 3D points automatically tracking the second plurality of 3D points within regions of the performer's face that fold or deform.

11. The method of claim 9 further comprising:

the first plurality of 3D points automatically tracking the second plurality of 3D points that include some or all parts of the eyes, lips, or teeth.

12. The method of claim 9 wherein the 3D mesh for one or more time intervals corresponds to a facial expression.

13. The method of claim 9 further comprising:

capturing the surface of the performer's face in visible light by the same plurality of cameras or one or more different cameras.

14. The method of claim 9 further wherein the time intervals are not successive frame times.

15. The method of claim 9 further comprising:

correlating the 2D frames at a first resolution, and then correlating the 2D frames at a second resolution that is a higher resolution than the first resolution.

16. A system comprising:

a plurality of cameras, each capturing a plurality of 2D frames of some or all of a surface of a performer's face as the performer's face changes in some or all of the plurality of time intervals;

a processor that correlates the plurality frames from the plurality of cameras at the plurality of time intervals to create a high-resolution 3D mesh corresponding to a 3D shape of some or all of the performer's face at some or all of the time intervals;

wherein a first plurality of 3D points in the high-resolution 3D mesh automatically track a second plurality of 3D points within regions of the performer's face as they fold or deform.

17. The system of claim 16 wherein the second of 3D points on the surface of the performer's face are not identified by markers, applied to the performer's face.

18. The system of claim 16 wherein the first plurality of 3D points automatically track the second plurality of 3D points that include some or all parts of the eyes, lips, or teeth.

19. The system of claim 16 wherein the 3D mesh for one or more time intervals corresponds to a facial expressions.

20. The system of claim 16 wherein the surface of the performer's face in visible light is captured by the same plurality of cameras or one or more different cameras.

21. The system of claim 16 wherein the time intervals are successive frame times.

22. The system of claim 16 wherein at least some of the time intervals are not successive frame times.

23. The system of claim 16 wherein the processor correlates the 2D frames at a first resolution, and then correlates the 2D frames at a second resolution that is a higher resolution than the first resolution.

24. A method comprising:

correlating frames from a plurality of cameras at a plurality of time intervals, each camera capturing a plurality of 2D frames of some or all of a surface of a performer's face as the performer's face changes in some or all of the plurality of time intervals;

creating a high-resolution 3D mesh corresponding to a 3D shape of the surface of some or all of the performer's face at some or all of the time intervals;

a first plurality of 3D points in the high-resolution 3D mesh automatically tracking a second plurality of 3D points on the surface of the performer's face;

wherein the first plurality of 3D points automatically track the second plurality of 3D points within regions of the performer's face that fold or deform.

25. The method of claim 24 wherein the second plurality of 3D points on the surface of the performer's face are not identified by markers applied to the performer's face.

26. The method of claim 24 further comprising:

the first plurality of 3D points automatically tracking the second plurality of 3D points that include some or all parts of the eyes, lips, or teeth.

27. The method of claim 24 wherein the 3D mesh for one or more time intervals corresponds to a facial expressions.

28. The method of claim 24 further comprising:

capturing the surface of the performer's face in visible light by the same plurality of cameras or one or more different cameras.

29. The method of claim 24 wherein the time intervals are not successive frame times.

30. The method of claim 24 further comprising:

correlating the 2D frames at a first resolution, and then correlating the 2D frames at a second resolution that is a higher resolution than the first resolution.

Continuity (7)
Continuation 16792116 · Feb 14, 2020
Continuation 15713601 · Sep 22, 2017
Continuation 14754651 · Jun 29, 2015
Division 14187759 · Feb 24, 2014
Division 11255854 · Oct 20, 2005
Provisional Application 60724565 · Oct 7, 2005
Related Publication 20210049803A1 · Feb 18, 2021