1. Animating Human Athletes By J.K. Hodgkins and W.L. Wooten Arjun Rihan CS 99K: Digital Actors

2. Introduction n People are skilled at perceiving the subtle details of human motion n If synthesized human motion is to be compelling, it is necessary to create actors for computer animations and virtual environments that are realistic

3. Algorithmic Approach n Control algorithms that allow a rigid-body human model to run, vault and ride a bicycle in various environments n Built from a common toolbox: state machines, inverse kinematics, etc.

4. Advantages n Can be easily modified to compute similar but different motions n Greater interaction possible, especially in virtual environments n Possible to generate secondary or composite motion

5. Disadvantages n Difficult to design n Range of parameter variation allowed is relatively narrow n Workstation speed limits their use. For example, the simulations show earlier run from 6 to 20 times slower than real time in virtual environments

6. Examples n Compare the actor to the human diver

7. Example n Notice the how the actor mimics reality by trying to regain balance after the jump

8. Dynamic Behaviors n Each simulation contains: n - the equations of motion for model and environment n - control algorithms for balancing, running, etc. n - graphical user interface for simple top-level parameter control

9. Dynamic Behaviors (contd.) n In the case of a gymnast performing a vault, the control system obtains the following parameters and then computes the required forces and positioning of the limbs from control algorithms

10. The Human Models n Rigid links connected by rotary joints with varying degrees of freedom n Examples of possible constraints on the degrees of freedom of the foot

11. Modeling Phases with State Machines n The distinct phases and corresponding changes in control actions are generated by a state machine n This is a schematic of the state machine for the runner n Transitions refer to the active leg n Active leg and idle leg keep alternating

12. Another State Machine - Gymnast n The state machine determines the control laws that are in effect for each phase of the vault

13. What This Means n The algorithms presented here enable an animator to generate motion for several dynamic behaviors

14. Evaluation n Through side-by-side comparison of video footage and animation, results appear to be good (What do you think?) n Comparison with biomechanical data is favorable

15. Evaluation (contd.) n A final form of evaluation would be a Turing test n Would involve direct comparison between simulated and human data on the same graphical model n Which motion would viewers prefer, given that that they wanted a more “natural” motion?

16. Next Steps n How can we make it easier to generate control algorithms for a new behavior? u By using a toolbox of general techniques to construct them as demonstrated here n How can we make the motion more natural? u Combine this approach with motion-capture and keyframing u Fine-tune the algorithms with human aesthetics

17. More Examples