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Computer Animation CS 445/645 Fall 2001
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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?
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Computer Animation
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Keyframing Traditional animation technique Dependent on artist to generate ‘key’ frames Additional, ‘inbetween’ frames are drawn automatically by computer
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Keyframing From “The computer in the visual arts”, Spalter, 1999 How are we going to interpolate?
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Linear Interpolation Simple, but discontinuous velocity
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Nonlinear Interpolation Smooth ball trajectory and continuous velocity, but loss of timing
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Easing Adjust the timing of the inbetween frames. Can be automated by adjusting the stepsize of parameter, t.
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Style or Accuracy? Interpolating time captures accuracy of velocity Squash and stretch replaces motion blur stimuli and adds life-like intent
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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
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More squash and stretch
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Anticipation and Staging Don’t surprise the audience Direct their attention to what’s important
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Follow Through Audience likes to see resolution of action Discontinuities are unsettling
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Combined
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Secondary Motion Characters should exist in a real environment Extra movements should not detract
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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
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Interpolation Strengths –Animator has exacting control (Woody’s face) Weaknesses –Interpolation hooks must be simple and direct Remember the problems with Euler angle interp? –Time consuming and skill intensive –Difficult to reuse and adjust
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Movies Cartoon Physics Homer3D
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Examples Sports video games –Madden Football Many movie characters –Phantom Menace Cartoons
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Motion Capture Strengths Exactly captures the motions of the actor –Michael Jordan’s video game character will capture his style Easy to capture data
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Motion Capture Weaknesses Noise, noise, noise! Magnetic system inteference Visual system occlusions Mechanical system mass Tethered (wireless is available now)
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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
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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
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Movies Animating Aliens Retargeting Motion – Siggraph ‘98 Siggraph ‘99 Papers Tape
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Examples Inanimate video game objects –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
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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
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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
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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
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Movies Humming Along Siggraph 2000
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