k-sketch: a “kinetic” sketch pad for novice animators
DESCRIPTION
K-Sketch: A “Kinetic” Sketch Pad for Novice Animators. Richard C. Davis SMU School of Information Systems Collaborators: Brien Colwell (NYU), James Landay (UW) NUS CS Seminar, Feb 25, 2009. How Would a Teacher Animate This?. How Would a Teacher Animate This?. Need Quick & Easy Animation!. - PowerPoint PPT PresentationTRANSCRIPT
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K-Sketch - R.C. Davis 1
Richard C. DavisSMU School of Information Systems
Collaborators: Brien Colwell (NYU), James Landay (UW)
NUS CS Seminar, Feb 25, 2009
K-Sketch: A “Kinetic” Sketch Pad for Novice Animators
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How Would a Teacher Animate This?
SO42-
SO42-
-e
-e
-e
-e
Zn(Z inc)anode
Cu(Copper)cathode
cell ce llmembrane
(Sulfate) (Sulfate)
Zn2+
Cu2+
1.10 V
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How Would a Teacher Animate This?
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Need Quick & Easy Animation!
Amateur ArtistsPlay in new mediumNeed a simple way to get started
ProfessionalsShare dynamic ideasNeed tool expressive enough for variety of tasks
Students & EducatorsLearn complex conceptsNeed to animate fast before or during class
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Users Need Animation “Paper” Properties of paper
Fast: Express ideas quickly Simple: Learn fast, focus on high-level
task Expressive: Handle wide variety of
tasks K-Sketch realizes this vision
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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Current Animation Tools Lacking
Child Tools Too slow
Professional Tools Too complex Focused on polish
Special Case Tools Too constraining
Sketchy (GoKnow)
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Current Animation Tools Lacking
Child Tools Too slow
Professional Tools Too complex Focused on polish
Special Case Tools Too constraining
Flash (Adobe)
PowerPoint (Microsoft)
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Current Animation Tools Lacking
Child Tools Too slow
Professional Tools Too complex Focused on polish
Special Case Tools Too constraining
Pivot Stick Figure Animator
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Solution: Informal Interfaces
Defer Details Focus on precision
distracts & slows down Precision often
unimportant
Sketched Input Hand drawn objects Motion imprecise
SILK (Landay & Myers 1995)
DENIM (Newman et al. 2003)
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Research Stops at Techniques How to choose techniques?
Visual Language Koka
(Takahashi, et al. 2005)
Physical Simulation
Assist (Alvarado & Davis 2001)
Demonstration Race Sketch
(Moscovich & Hughes 2001)
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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Interviews with Animators Seven animators
4 made short films 1 made web sites with Flash 2 made conference presentations
Wanted to work more in rough form Interested in prototyping
Storyboard from a film animator
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Interviews with Non-Animators
Occupation Domain Animation Descriptions
1. Education Student Biology Student exercise: meiosis
2. Education Student Physics Planetary motion
3. Mech. Eng. Professor
Engineering
Gears, molecular shifting
4. CS Grad. Student Dance Contra dance moves
5. Chemistry Professor ChemistryParticle collisions, rusting
reaction, battery reaction
6. ResearcherEngineerin
gMachine tread motion
7. Math Instructor Math Cantor set construction
8. Reading Tutor Reading Fun animations to motivate
9. Aeronautical Engineer
Engineering
Robot arm following a path
10. ManagerEngineerin
gBox sliding into casing
11. Researcher Geology Etalon noise
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Example: Particle Collisions
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Example: Contra Dance
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Example: Machine Tread
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Library of Usage Scenarios Complete usage scenarios
User task Animation that accomplishes the task
72 examples in library 27 from animators 23 from non-animators 22 from children (students of
animator) Identified 18 Animation Operations
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Examples of Animation Operations
Orient to Path
Trace
Move Relativ
e
CopyMotion
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Examples of Animation Operations
Orient to Path
Trace
Move Relativ
e
CopyMotion
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Examples of Animation Operations
Orient to Path
Trace
Move Relativ
e
CopyMotion
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Examples of Animation Operations
Orient to Path
Trace
Move Relativ
e
CopyMotion
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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Our Library is a Gold Mine Scenarios: breadth of applications
How many can we handle? Many approaches to each
Some require “extra” steps
Animation Ops Can we leave some out?
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Goals Optimization Constraints
Goals of “paper-like” interfaces Fast: Express ideas quickly Simple: Learn fast, focus on high-level task Expressive: Handle wide variety of tasks
Goals expressed as optimization Fast: Allow only a few extra steps Simple: Minimize # Anim Ops Expressive: Maximize # supported
animations
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Simplicity/Expressivity Tradeoff
Expressivity(More Supported Animations)
Simplicity(Less Anim Ops)
Look for point of diminishing returns
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Step 1: Code All 72 Animations
Break up: Animations “Features” Features “Approaches”
Required Anim Ops Number of “Extra Steps”
Battery Example Three Features (electrons, sulfate ions, switch) Two sulfate ion approaches
1. Appear + Translate + Disappear + Copy (6 steps)2. Appear + Translate + Disappear (12 steps, 6 extra)
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Step 2: Find Best Operation Sets
Optimization program For N = 1 to 72 animations
Find smallest set of operations That supports N animations
No approaches with >4 extra steps
Examples (Appear, Translate, Disappear, Copy) supports
Battery Use fastest approach for Sulfate ion
(Appear, Translate, Disappear, Morph) does not Only available approach for ion has 6 extra steps
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Optimization Results
0
2
4
6
8
10
12
14
16
18
0% 20% 40% 60% 80% 100%
Supported Animations (Expressivity)
# A
nim
ati
on
Op
era
tion
s(S
imp
licit
y
)
0
2
4
6
8
10
12
14
16
18
DiminishingReturns
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Scenarios Supported
15%
21% 28%36%
46%
51%
68%
75% 79% 86%93%
97%
100%
1.Translate
2.Scale
3.Rotate
4.Set Timing
5.Move Relative
6.Appear
7.Disappear
8.Trace
9.Repeat Motion
10.Copy Motion
11.Define Cels
12.Morph
13.Physically Sim.
14.Interpolate
15.Move Forw/Back
16.Deform
17.Move Limb
18.Orient To Path
An
imati
on O
pera
tions
Optimization Results: Detailed View
Black: operation is needed in all minimal sets
Grey: operation is in some, but not all sets
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K-Sketch Strikes Best Balance Existing tools omit
Demonstration Trace
K-Sketch Omits Cel-based animation Deformation Precision
ToolSupported Scenarios
K-Sketch 81%
Flash 63%
PowerPoint
47%
TAB Lite 32%
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Interface Optimization Works Data-driven
Feature decisions often subjective Scenario data brings objectivity
Before application release Better than frequency counts Find best operations sooner
Widely applicable Code works on any data set Current algorithm parallelizes easily
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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K-Sketch System
Demo
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K-Sketch Key Features Demonstration
Combines many ops in one Visible motion paths
Easy coordination/editing of motions Ability to add relative motions
Correction interface resolves ambiguity Copy motions
Scale up animations quickly Simplified timeline
Easily change timing of events
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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What Should We Compare With?
Professional tools for different users Flash: Designers PowerPoint: Presenters
Research tools incomplete Only interaction techniques Not our main contribution
Our Strategy Use best tool for situation
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Summative Evaluation Goals of “paper-like” interfaces
Fast: Express ideas quickly Simple: Learn fast, focus on high-level
task Expressive: Handle wide variety of tasks
Evaluation Strategy Lab Study 1: How fast, How simple? Lab Study 2: How expressive? Case Studies: How is work affected?
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Laboratory Study 1
Evaluate speed and simplicity 16 novices (varied professions,
ages) Within-subjects experiment:
PowerPoint General-purpose Targets novices
Practice task plus two from library
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Laboratory Study 1: Tasks Task A
Particle Collision
Task B Dance Maneuver
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Study 1 Results: K-Sketch Fast
K-SketchPowerPoi
nt
M SD M SD p-val
1. Task Time (min.) 6.8 3.5 19.6 11.0p<.00
1
2. Fast? (1–7, 1 = fastest)
2.8 1.4 4.5 1.10p<.00
1
K-Sketch was faster (statistically significant) Tasks took 1/3 the time Felt faster
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Study 1 Results: K-Sketch Simple
K-SketchPowerPoi
nt
M SD M SD p-val
3. Practice Time (min.) 26.4 4.8 43.5 11.4p<.00
1
4. Easy? (1–7, 1 = easiest)
2.1 1.4 4.3 0.8p<.00
1
5. NASA-TLX (1–100) 32 18 57 16p<.00
1
K-Sketch was simpler (statistically significant) Half the practice time needed Felt easier Lower cognitive load
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Study 1 Results: Comfort Level
K-SketchPowerPoi
nt
M SD M SD p-val
6. Comfort Sharing (1–7)
5.2 1.1 4.9 1.1 p=.38
7. Comfort Creating (1–7)
5.5 1.1 4.1 1.3p=.00
2
K-Sketch no worse in sharing with others
More comfortable creating with K-Sketch (statistically significant)
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Part. 8: Dance Maneuver PowerPoint
15 min. 24 sec. Told: avoid precision Still perfected paths
K-Sketch 4 min. 38 sec. More comfortable
showing & creating
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Laboratory Study 2 Evaluate Expressivity 7 novices (students, various ages) 9 tasks chosen randomly Compare with “The TAB Lite”
“Supports” only 32% of scenarios Two 3-hour sessions with each tool Use pen in both conditions
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Study 2: Handling Varied Tasks
K-Sketch handles more important AnimOps Speed improves when AnimOps missing from TAB
-100%
-50%
0%
50%
100%
150%
200%
250%
Face
Sunrise
Gears
Ant
Juggle
Acrobat
Planes
Fairy
Waves
Task
K-S
ke
tch
Sp
ee
d-u
p
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Study 2: Creative Improvisation
K-Sketch required less paper sketches/notes 7% of K-Sketch tasks 41% of TAB Lite tasks
K-Sketch required no calculations 5 of 7 participants struggled with math in
TAB
“With K-Sketch, I didn’t have to draw plans or do calculations, which leads me to believe it is a more ‘intuitive’ tool.”
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Study 2: Evidence of Expressivity
Nine random tasks with K-Sketch Tasks cover 17 of 18 Animation Ops Speed due to expressivity
Average 61% faster than TAB Only 3 of 63 trials incomplete (12 for TAB)
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Case Study #1 “Zero button mouse” design
Prototyping animated feedback Quickly evaluated 25 designs
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Case Study #2 High school learning exercises
3 months, 5 classes, 106 students Better recall & motivation Misconceptions clearer
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K-Sketch Deployment Download at
http://www.k-sketch.org Over 600 downloads in first 1½
months Send us feedback!
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K-Sketch: Outline Related Work Field Studies Interface Optimization K-Sketch System Evaluations Future Work
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Generalized Interface Optimization Formally define the coding process
How to assemble high quality library How to manage evolution of primitive
ops Improve handling of speed constraint
Optimize on speed variable Add weights to primitive ops
Build tools for coding & processing Improve scalability
Apply technique to new domains
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Sketching Simulations/Games Rough End-user Simulations
For learning and fun Animation is first step
NSF CreativeIT SGER ’07
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Manage Ideas Through Life Cycle
Polished Final Product
Collecting & Sharing Notes NotePals
Can’t move data across
Notes with behavior bridge the gap Tools for
transitioning
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Contributions Concepts and Techniques
Analysis of animation usage scenarios Novel interface optimization method
Artifacts K-Sketch design and implementation
Experimental Results 3x speed-up over formal tool
(PowerPoint) Helps users avoid focusing on precision Expresses a wide variety of animations
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K-Sketch: A “Kinetic” Sketch Pad for Novice Animators
Richard C. DavisSMU School of Information Systems
[email protected]://www.mysmu.edu/faculty/rcdavis
http://www.k-sketch.org