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Animation Low-Level behaviors Overview Keyframing Motion Capture Simulation Low-Level Behaviors Keyframing Motion Capture Simulation Generating Motion What matters? Quality of motion appropriate for rendering style and frame rate Controllable from UI Controllable from AI

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Animation l.jpg

Animation

Low-Level behaviors Overview

Keyframing

Motion Capture

Simulation

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Low level behaviors l.jpg
Low-Level Behaviors

  • Keyframing

  • Motion Capture

  • Simulation

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Generating motion l.jpg
Generating Motion

  • What matters?

    • Quality of motion appropriate for rendering style and frame rate

    • Controllable from UI

    • Controllable from AI

    • Personality of the animated character

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Keyframing l.jpg
Keyframing

  • Fine level of control

  • Quality of motion depends on skill of animator

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Motion capture l.jpg
Motion Capture

  • Natural-looking motion

  • Hard to generalize motions

    • Registration is difficult

    • “Weightless” according to professional animators

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Motion capture images courtesy microsoft motion capture group l.jpg
Motion CaptureImages courtesy Microsoft Motion Capture Group

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Simulation (Broadly Defined)

  • Physics is hard to simulate

  • Pseudo-physics is somewhat hard

  • Control is very hard

  • Gives Generalization + Interactivity

Desired

Behavior

Forces and Torques

Model

Numerical Integrator

User/AI

Control

State

Graphics

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When to use what method l.jpg
When to Use What Method?

  • Keyframing

    • Sprites and other simple animations

    • Non-human characters

    • Coarse collision detection

  • Motion Capture

    • Human figures

    • Subtle motions, long motions

  • Simulation

    • Passive simulations

    • When interactivity w/ motion is important

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Keyframing

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Keyframing

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Keyframing

  • Fine level of control

  • Quality of motion depends on skill of animator

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Hand Drawn Animation -- 2D

  • Sketches

  • Pencil tests

  • Inking

  • Coloring

  • Digitize to sprites

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Computer Animation: 2D or 3D

  • Sketches

  • Models and materials

  • Key configurations

  • Playback of motion or render to sprites

Improv

Ken Perlin, NYU

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The development process:

Adjust trajectory

Playback motion

Parameters:

Locations

Joint angles

Shape -- flexible objects

Material properties

Camera Motion

Lighting

Keyframing

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Keyframing Interpolation

  • Inbetweening

v

1,2,3 4 5 6 7,8,9…

Linear

time

v

1,2,3 4 5 6 7,8,9…

Slow in, Slow out

time

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Key Frames

1

2

3

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Key Frames

  • Timeline

  • 1 2 3 3 1

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Inbetweening

  • Frame dependent (“wrong”) slow-in/out

    • Iterate once per frame

    • This is a variant on the Infinite Impulse Response (IIR) filter:

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Inbetweening

  • Frame-Independent (“right”) slow in/out

    • Compute acceleration a

Time of last frame

Time

Tend

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Spline-driven Animation

y

x,y = Q(u)

for u:[0,1]

  • Equal arc lengths

  • Equal spacing in u

x

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Reparameterize Arc Length

  • S= A(u) = arc length

  • Reparam:

  • Find:

    Bisection search for a value

    of u where A(u) = S with a

    numerical evaluation of A(u)

    (Details in Watt & Watt)

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Keyframing -- Constraints

  • Joint limits

  • Position limits

  • Inverse kinematics

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Kinematics

  • The study of motion without regard to the forces that cause it

Draw graphics

Specify fewer Degrees Of

Freedom (DOF)

More intuitive control of DOF

Pull on hand

Glue feet to ground

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What makes IK Hard?

  • Many DOF -- non-linear transcendental equations

  • Redundancies

    • Choose a solution that is “closest” to the current configuration

    • Move outermost links the most

    • Energy minimization

    • Minimum time

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IK Difficulties

  • Singularities

    • Equations are ill-conditioned near singularities

    • High state-space velocities for low Cartesian velocities

  • Goal of “Natural Looking” motion

    • Minimize jerk (4th derivative)

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Motion Capture

  • What do we need to know?

    • X, Y, Z

    • Roll, Pitch, Yaw

  • Errors cause

    • Joints to come apart

    • Links grow/shrink

    • Bad contact points

  • Sampling Rate and Accuracy

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Motion Capture

  • Goals:

    • Realistic motion

    • Lots of different motions (300-1000)

    • Contact

  • Appropriate game genres

    • Sports

    • Fighting

    • Human characters

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Applications

Movies, TV

Video games

Performance animation

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Plan out Shoots Carefully

  • Know needed actions (80-100 takes/day)

    • Bridges between actions

    • Speed of actions

    • Starting/ending positions

  • Hire the right actor

    • Watch for idiosyncrasies in motion

    • Good match in proportions

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Sensor Placement

  • Place markers carefully

    • Capture enough information

    • Watch for marker movement

  • Check data part way through shoot

  • Videotape everything!

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Technology

  • Numerous technologies

  • Record energy transfer

    • Light

    • Electromagnetism

    • Mechanical skeletons

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Technology

  • Passive reflection – Peak Performance Tech

    • Hand or semi-automatically digitized

    • Video

    • Time consuming

  • Issues

    • No glossy or reflective materials

    • Tight clothing

    • Marker occlusion by props

    • High frames/sec

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Technology

  • Passive reflection --Acclaim, Motion Analysis

    • Automatically digitized

    • 240Hz

    • Not real-time, Correspondence

    • 3+ markers/body part

    • 2+ cameras for 3D position data

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Technology

  • Vicon Motion Systems

    • Retroreflective paint on reflectors

    • Lights on camera

    • Very high contrast markers

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Technology

  • Active light sources -- Optotrak

    • Automatically digitized

    • 256 markers

    • 3500 marker/sec

    • Real-time

    • Specialized cameras

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Technology

  • Electromagnetic Transducers

    • Ascension Flock of Birds, etc

    • Polhemus Fastrak, etc

  • Limited range/resolution

    • Tethered (cables to box)

    • Metal in environment (treadmill, Rebar!)

    • No identification problem

    • 6DOF Realtime

    • 30-144 Hz 13-18 markers

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Technology

  • Exoskeleton + angle sensors

    • Analogous

    • Tethered

    • No identification problem

    • Realtime - 500Hz

    • No range limit - Fit

    • Rigid body approximation

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Dataglove

Low accuracy

Focused resolution

Monkey

High accuracy

High data rate

Not realistic motion

No paid actor

Technology

Mechanical motion capture

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Technology

  • Technology issues

    • Resolution/range of motion

    • Calibration

    • Accuracy

    • Occlusion/Correspondence

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Animation issues l.jpg
Animation Issues

  • Style

  • Scaling

  • Generalization

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Resolution l.jpg
Resolution

  • Positioning of camera

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Markers, Calibration

  • Marker Placement

    • Location should move rigidly with joint

    • Stay away from bulging muscles, loose skin

    • Shoulders: Skeletal motion not closely tied to skin motion

  • Calibration

    • Zero position

    • Fine calibration by hand

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Calibration l.jpg
Calibration

  • Finding Joint Locations

    • Move markers to joint centers

      • Assume rigid links, rotary joints

  • Shoulder?

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Calibration

  • Extract best limb lengths

  • Use estimator to compute limb length

  • Minimize or reject outliers

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Calibration

  • Example estimator:

    • 508 frames of walking

    • 6 bad frames

    • Collarbone to shoulder:

      • Hand editing: 13.3cm

      • Estimator: 13.2cm

      • Arithmetic mean: 14.1cm

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Accuracy

  • Marker movement

  • Noise in sensor readings

  • Skew in measurement time

  • Environment restrictions

  • Frame rate

    • High frame rate allows good filtering

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Camera Calibration

  • Internal camera parameters

    • Optical distortion of lens

  • External parameters

    • Position and orientation

  • Correlation between multiple cameras

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Model based techniques l.jpg
Model-Based Techniques

  • Restricted search space for markers

  • Dynamics (velocity integration)

    • No infinite accelerations

  • Model of behavior

  • Model of bodies of occlusion

    • Objects don’t pass through each other

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Scaling animation l.jpg
Scaling Animation

  • Contact

  • Movement style

  • Inverse kinematics

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Generalizating Animation

  • Interpolation Synthesis for Articulated Figure Motion

  • Wiley and Hahn

  • IEEE CG&A v17#6

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Generalizating Animation

  • Keyframes as constraints in a smooth deformation

  • Keyframe placing the ball on the racket at impact

    Motion Warping

    Witkin and Popovic, SIGGRAPH’95

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Generalizating Animation

  • Motion Editing With Spacetime Constraints

    • Michael Gleicher

    • 1997 Symposium on Interactive 3D Graphics

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Blending Animations

  • Efficient Generation of Motion Transitions Using Spacetime Constraints

    • Rose, Guenter, Bodenheimer, Cohen

    • Siggraph ’96

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Simulation l.jpg
Simulation

  • Modeling the real world with simple physics

    • Realism

    • A set of rules

    • Better interactivity

  • Objects or Characters

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Passive -- No muscles or motors

Active -- Internal source of energy

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Equations of Motion

  • Water

  • Explosions

  • Rigid body models

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Control Systems

  • Wide variety of behaviors

  • Transitions between behaviors

  • Controllable by AI or UI

  • Robust

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Generating motion70 l.jpg
Generating Motion

  • What matters?

    • Quality of motion appropriate for rendering style and frame rate

    • Controllable from UI

    • Controllable from AI

    • Skills of the animated character

    • Personality of the animated character

CS 4455


Keyframing71 l.jpg
Keyframing

  • Fine level of control

  • Quality of motion depends on skill of animator

CS 4455


Motion capture72 l.jpg
Motion Capture

  • Natural-looking motion

  • Hard to generalize motions

    • Registration is difficult

  • Often seems “weightless” – Bill Kroyer, Rhythm & Hues

CS 4455


Simulation broadly defined73 l.jpg
Simulation (Broadly Defined)

  • Physics is hard to simulate

  • Pseudo-physics is somewhat hard

  • Control is very hard

  • Gives Generalization + Interactivity

Desired

Behavior

Forces and Torques

Model

Numerical Integrator

User/AI

Control

State

Graphics

CS 4455


When to use what method74 l.jpg
When to Use What Method?

  • Keyframing

    • Sprites and other simple animations

    • Non-human characters

    • Coarse collision detection

  • Motion Capture

    • Human figures

    • Subtle motions, long motions

  • Simulation

    • Passive simulations

    • When interactivity w/ motion is important

CS 4455


Integration of technologies l.jpg
Integration of Technologies

  • Layering

    • Add hand/finger motion later

    • Facial animation

  • Use keyframing to modify data

    • Fix holes in data

  • Use motion capture to drive simulation

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