Pose tracking pipeline

1. A method of computer modeling a human subject, the method comprising:

receiving from a source a depth image of a scene including the human subject, the depth image including a depth for each of a plurality of pixels;

identifying pixels of the depth image that image the human subject; and

deriving from the identified pixels of the depth image one or more machine readable data structures representing the human subject as a body model including a plurality of different geometric shapes, each of the plurality of shapes represented by a centroid position of that shape.

2. The method of claim 1 , where the plurality of different geometric shapes include one or more spheres.

3. The method of claim 2 , where each of the one or more spheres is represented by a position variable defining a centroid position of that sphere.

4. The method of claim 3 , where each of the one or more spheres is represented by a size variable defining a size of that sphere.

5. The method of claim 1 , where each of the plurality of different geometric shapes is represented by one or more size variables defining a size of that shape and one or more position variables defining a position of that shape.

6. The method of claim 1 , further comprising deriving from the body model a skeleton including a plurality of skeletal points, each skeletal point having a three-dimensional location.

7. The method of claim 1 , where the source includes a structured light depth sensor.

8. The method of claim 1 , where the source includes a time-of-flight depth sensor.

9. A method of computer modeling a human subject, the method comprising:

receiving from a source a depth image of a scene including the human subject, the depth image including a depth for each of a plurality of pixels; and

modeling the human subject with a plurality of shapes having a same geometric shape and two or more different sizes, each of the plurality of shapes characterized by a centroid defining a position of that shape within a volume occupied by the human subject.

10. The method of claim 9 , where the plurality of shapes are a plurality of spheres.

11. The method of claim 10 , where the machine readable position variable for each of the plurality of spheres defines a centroid position of that sphere.

12. The method of claim 10 , where each of the plurality of spheres is represented by a size variable defining a size of that sphere.

13. The method of claim 9 , further comprising deriving from the plurality of shapes a skeleton including a plurality of skeletal points, each skeletal point having a three-dimensional location.

14. The method of claim 9 , where the source includes a structured light depth sensor.

15. The method of claim 9 , where the source includes a time-of-flight depth sensor.

16. The data-holding subsystem of claim 15 , where at least one of the plurality of shapes has a different geometric shape than at least one other of the plurality of shapes.

17. A data-holding subsystem holding instructions executable by a logic subsystem to:

receive from a source a depth image of a scene including a subject; and

model the subject with a plurality of shapes, each of the plurality of shapes characterized by a centroid defining a position of that shape such that the plurality of shapes collectively occupy a volume of the subject.

18. The data-holding subsystem of claim 17 , where all of the plurality of shapes are a same geometric shape and a same size.

19. The data-holding subsystem of claim 17 , where the source includes a structured light depth sensor.

20. The data-holding subsystem of claim 17 , where the source includes a time-of-flight depth sensor.