Computer Animation CS 446 September 5, 2001.

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Presentation transcript:

Computer Animation CS 446 September 5, 2001

Let’s talk about computer animation Must generate 30 frames per second of animation (24 fps for film) Issues to consider: Is the goal to replace or augment the artist? What does the artist bring to the project? Is the scene/plot fixed or responsive to user? What can we automate?

Computer Animation

Keyframing Traditional animation technique Dependent on artist to generate ‘key’ frames Additional, ‘inbetween’ frames are drawn automatically by computer

Keyframing How are we going to interpolate? From “The computer in the visual arts”, Spalter, 1999

Linear Interpolation Simple, but discontinuous velocity

Nonlinear Interpolation Smooth ball trajectory and continuous velocity, but loss of timing

Easing Adjust the timing of the inbetween frames. Can be automated by adjusting the stepsize of parameter, t.

Style or Accuracy? Interpolating time captures accuracy of velocity Squash and stretch replaces motion blur stimuli and adds life-like intent

Traditional Motivation Ease-in and ease-out is like squash and stretch Can we automate the inbetweens for these? “The Illusion of Life, Disney Animation” Thomas and Johnson

More squash and stretch

Anticipation and Staging Don’t surprise the audience Direct their attention to what’s important

Follow Through Audience likes to see resolution of action Discontinuities are unsettling

Combined

Secondary Motion Characters should exist in a real environment Extra movements should not detract

Interpolation Many parameters can be interpolated to generate animation Simple interpolation techniques can only generate simple inbetweens More complicated inbetweening will require a more complicated model of animated object and simulation

Interpolation Strengths Weaknesses Animator has exacting control (Woody’s face) Weaknesses Interpolation hooks must be simple and direct Time consuming and skill intensive Difficult to reuse and adjust

Movies Cartoon Physics Homer3D

Examples Sports video games Many movie characters Cartoons Madden Football Many movie characters Phantom Menace Cartoons

Motion Capture Strengths Exactly captures the motions of the actor Michael Jordan’s video game character will capture his style Easy to capture data

Motion Capture Weaknesses Noise, noise, noise! Magnetic system inteference Visual system occlusions Mechanical system mass Tethered (wireless is available now)

Motion Capture Weaknesses Aligning motion data with CG character Limb lengths Idealized perfect joints Reusing motion data Difficult to scale in size (must also scale in time) Changing one part of motion

Motion Capture Weaknesses Blending segments Motion clips are short (due to range and tethers) Dynamic motion generation requires blending at run time Difficult to manage smooth transition

Movies Animating Aliens Retargeting Motion – Siggraph ‘98

Examples Inanimate video game objects Special effects GT Racer cars Soapbox about why this is so cool Special effects Explosions, water, secondary motion Phantom Menace CG droids after they were cut in half

Procedural Animation Very general term for a technique that puts more complex algorithms behind the scenes Technique attempts to consolidate artistic efforts in algorithms and heuristics Allows for optimization and physical simulation

Procedural Animation Strengths Animation can be generated ‘on the fly’ Dynamic response to user Write-once, use-often Algorithms provide accuracy and exhaustive search that animators cannot

Procedural Animation Weaknesses We’re not great at boiling human skill down to algorithms How do we move when juggling? Difficult to generate Expensive to compute Difficult to force system to generate a particular solution Bicycles will fall down

Movies Humming Along