Animating Human Athletes
Post on 23-Jan-2016
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Animating Human Athletes
By J.K. Hodgkins and
W.L. Wooten
Arjun Rihan
CS 99K: Digital Actors
Introduction People are skilled at perceiving the
subtle details of human motion If synthesized human motion is to
be compelling, it is necessary to create actors for computer animations and virtual environments that are realistic
Algorithmic Approach Control algorithms that allow a
rigid-body human model to run, vault and ride a bicycle in various environments
Built from a common toolbox: state machines, inverse kinematics, etc.
Advantages Can be easily modified to compute
similar but different motions Greater interaction possible,
especially in virtual environments Possible to generate secondary or
composite motion
Disadvantages
Difficult to design Range of parameter variation
allowed is relatively narrow Workstation speed limits their use.
For example, the simulations show earlier run from 6 to 20 times slower than real time in virtual environments
Examples
QuickTime™ and aCompact Video decompressorare needed to see this picture.
Compare the actor to the human diver
Example
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Notice the how the actor mimics reality by trying to regain balance after the jump
Dynamic Behaviors
Each simulation contains: - the equations of motion for model
and environment - control algorithms for balancing,
running, etc. - graphical user interface for simple
top-level parameter control
Dynamic Behaviors (contd.)
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
The Human Models
Rigid links connected by rotary joints with varying degrees of freedom
Examples of possible constraints on the degrees of freedom of the foot
Modeling Phases with State Machines The distinct phases and corresponding
changes in control actions are generated by a state machine
This is a schematic of the state machine for the runner
Transitions refer to the active leg
Active leg and idle leg keep alternating
Another State Machine - Gymnast
The state machine determines the control laws that are in effect for each phase of the vault
What This Means The algorithms presented here
enable an animator to generate motion for several dynamic behaviors
Evaluation
Through side-by-side comparison of video footage and animation, results appear to be good (What do you think?)
Comparison with biomechanical data is favorable
Evaluation (contd.)
A final form of evaluation would be a Turing test
Would involve direct comparison between simulated and human data on the same graphical model
Which motion would viewers prefer, given that that they wanted a more “natural” motion?
Next Steps
How can we make it easier to generate control algorithms for a new behavior? By using a toolbox of general techniques to
construct them as demonstrated here How can we make the motion more natural?
Combine this approach with motion-capture and keyframing
Fine-tune the algorithms with human aesthetics
More Examples
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