Animation
CS 551 / 651
Hodgins et al., 1998
Perception of Physically
Simulated Humans
Perception
How should we render our objects?
• To what end?
– Verisimilitude
– Mechanical accuracy
– Impressionism
• What about motion?
Is simplicity better?
Advantages
• Abstraction is easier
• Obfuscations are removed
Disadvantages
• Complementary features are removed
– Edges, critical features
• May look “wrong”
Is complexity better?
Advantages
• Details provide perceptual cues
• This is the way we perceive things in real world
Disadvantages
• Difficult to get the details right
• May distract from basic motion
We have no idea…
We turn to different experts
• Psychologists
• Automated computer vision
Psychologists
Kubovy and Proffitt @ UVa
• Perception of patterned dot animations
– Models of perception
• Perception as it relates to action
– We perceive because it helps us to act
Attacks the perception question within welldefined psychological models
Computer Vision
Martin and Acton @UVa
• Low-level vision
– How do we detect edges, shadows, primitives
• High-level vision
– How do we compose “things” from primitives
Still no solid answers
Vision and psychology provide models of
perception that influence graphics
Graphics permits isolated experimentation
with perception models
The three fields move forward together
What’s amazing about us?
Perceiving friends
• Just two moving lights on ankles is enough
• Just two seconds is required
– Johansson (1973) Vanrie & Verfaillie (2004)
Perceiving pendula
• Humans thought moving dots were connected via
flexible bar, not rigid pendulum
Hodgins’ comparison
Is there a difference?
Observational tests
Torso rotation
• Keep head looking forward, but rotate torso and arms
Arm Motion
• Make arm swing more forward / backward
– Adjust dynamics accordingly
– How much?
Noise
• Randomly perturb joint angles (waist, shoulders, neck)
– No dynamics
– How much?
How the simulation works
Experimental protocol
Watch animations in pairs
• 4 seconds of one then 4 seconds of a mate
Indicate similarity or difference within pair
• forced choice
• Could you forget what first looked like?
Approx. 25 people per condition
Varied the order
• Avoids ordering effects (learning during experiment)
Experimental protocol
Animations rendered in same way
• Could this have made a difference?
– Is there a rendering that is conducive to stick
figures?
– What tricks would people use to identify motions?
Played from VHS at 30 fps
• Can’t have any effects from rendering blips
Results
On average, people were better with manH
Results
But how did rendering affect each person’s
ability?
There’s a trick!
Take-away messages
Don’t read too much into these results
• Each experiment may be different
• More detailed model was also more human-like
Standardization of animation environments
might be good for comparison
• Difficult to compare improvements from year to year
What else matters?
Camera movement
Ground plane
Motion blur
Secondary motion (clothing / hair)
Shadows
Additional commentary
Experiments are essential for graphics
• Yet rarely conducted
• How is graphics evaluated?
– The SIGGRAPH “aaahhhh” factor
Additional commentary
Creating experiments is dicey business
• Have to include psychologists who are experts of
experiment design
• Make sure enough subjects are included
• You need to understand the domain so well that you
know the answer before the experiments are
complete
– Many pretrials were conducted to refine amounts of
noise to add (to avoid making it too easy or hard)
Follow-up paper
Bodenheimer et al., 1999 Eurographics
Animation Workshop
How does noise influence perception?
How to add noise to simulation?
Sensors
• When the arm reaches angle q, trigger reaction
Control gains
• How stiff/strong are the muscles
Output torques
• How regular and well-behaved are the muscles
Control parameters
• When does the arm swing backwards
Output torques
Noise inserted here didn’t work well
• Instantaneous noise was quickly corrected with
subsequent countertorques
What kind of noise?
Variability of human motion is tied to large
movements of the body
• Not a random sinusoidal noise function
• Not a white noise
Experimental scenario
Watch 10 movies of varying noise and select
the one that looks most “natural”