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OptiMo:
Optimization-Guided Motion Editing
for Keyframe Character Animation
Yuki Koyama & Masataka Goto
Optimization Techniques:
- Powerful
- Used in computer science and engineering
https://en.wikipedia.org/wiki/Mathematical_optimization
How can animators utilize optimization techniques
for motion editing effectively?
We propose
“Optimization-Guided Motion Editing”
Background: How Do Animators
Create Motions?
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
How Do Animators Create Motions?
7
1. Keyframing 2. Curve Editing
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
How Do Animators Create Motions?
8
1. Keyframing 2. Curve Editing
Define key poses at
several keyframes
Adjust interpolation curves 

(how key poses are interpolated
between keyframes)
frame = 4 frame = 14
…
Time
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
How Do Animators Create Motions?
9
1. Keyframing 2. Curve Editing
Define key poses at
several keyframes
frame = 4 frame = 14
…
Our Target
Adjust interpolation curves 

(how key poses are interpolated
between keyframes)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Curve Editing is Important for Nuances
10
frame = 4 frame = 14
frame = 24 frame = 34
Even with the same
keyframing, motions
could be very different
in nuances
Difficulties in Curve Editing
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Difficulties in Curve Editing
12
Unintuitive (indirect)
effects
Need to play motions
every time manipulating
handles
Many parameters
High-dimensional
search task
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Difficulties in Curve Editing
13
Unintuitive (indirect)
effects
Need to play motions
every time manipulating
handles
Many parameters
High-dimensional
search task
A Possible (?) Solution: 

Naïve Optimization
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Optimization for Full Automation?
15
Optimization can fully automate the task, 

but results are not always satisfactory (no control…)
Optimization-Guided Motion Editing
Live Demo!
Design Goals:
What Should be Considered for
Effective Interaction?
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
18
?
Blackbox
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
19
1. Transparent
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
20
1. Transparent
Original
motion
Optimal
motion
Feature: Optimization Process Visualization (for Transparency)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
21
1. Transparent
Original
motion
Optimal
motion
Feature: Cost Visualization (for Transparency)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
22
1. Transparent
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
23
1. Transparent
2. Controllable
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
24
1. Transparent
2. Controllable
Original
motion
Optimal
motion
Feature: Interactive Regularization (for Controllability)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
25
1. Transparent
2. Controllable
Original
motion
Optimal
motion
Feature: Time-Varying Cost Control (for Controllability)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
26
1. Transparent
2. Controllable
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
27
1. Transparent
2. Controllable
…
3. Editable
Manual revision
allowed
Original
motion
Optimal
motion
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
28
1. Transparent
2. Controllable
…
3. Editable
Manual revision
allowed
Original
motion
Optimal
motion
Opt.
Control handles
Preserved
Feature: Preservation of Control Handles (for Editability)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
29
1. Transparent
2. Controllable
…
3. Editable
Manual revision
allowed
Original
motion
Optimal
motion
Opt.
Control handles
Preserved
Different arrangement
Different data structure
Feature: Preservation of Control Handles (for Editability)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Three Design Goals
30
1. Transparent
2. Controllable
…
3. Editable
Manual revision
allowed
Original
motion
Optimal
motion
Math: How to Formulate
Optimization with Controllability
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Optimization with Controllability
32
min
x
⇢Z
C(x, t)dtTypical
optimization
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Optimization with Controllability
33
min
x
⇢Z
wcost
(t)C(x, t)dt + wreg
D(x, xinit
)
min
x
⇢Z
C(x, t)dt
Control by
time-varying cost weight
Control by
regularization weight
Typical
optimization
Controllable
optimization
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Optimization with Controllability
34
min
x
⇢Z
wcost
(t)C(x, t)dt + wreg
D(x, xinit
)
min
x
⇢Z
C(x, t)dt
Control by
time-varying cost weight
Control by
regularization weight
Adjusted in real time
Typical
optimization
Controllable
optimization
Example Usage Scenarios
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Example: Fox Tail
• #parameters: 27
• Rig: Forward kinematics (FK)
36
Example: Fox Tail
Initial motion
- Too robotic…
Let’s apply the (naïve)
optimization first
Example: Fox Tail
Naïve optimization
- Too much changed!
Let’s control it by
regularization
Example: Fox Tail
Optimization
with regularization
- Looks good!!
Inspiration:
How about making
the swing speedier?
Example: Fox Tail
Optimization
with regularization
& time-varying cost
Time-varying
cost weight
Validation: Interview with
Professional Animators
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Informal Interview
Goals
• Validation of our approach (design goals, interactions, etc.)
Participants
• 2 professional animators (A1 & A2) who are familiar with 3D
character animation authoring
Procedure
• Explain our design goals, explain our system features, and
ask feedback comments (approx. 1 hour)
42
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Results
Editability
• Both A1 and A2 loved editability, which was described
“indispensable” (A1)
Transparency
• We observed that both A1 and A2 easily understood the concept of
optimization by just seeing the visualizations
Controllability
• All features on controllability were strongly appreciated
• The interactivity makes the adjustment “easier” and “less
stressful” (A1)
43
Discussions
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Related Work: Motion Editing Techniques
45
[Kazi+16][Glauser+16]
Tangibles
[Choi+16]
Sketches Principles Optimization
Ours
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Related Work: Design Interface with Optimization
46
[Koyama+14] [Umetani+14] Ours
Photo color
adjustment, etc.
Paper
airplanes
Character
motions
[O’Donovan+15]
Graphic
layout
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Future Work
47
E.g., architecture design
[Kilian+17]E.g., Autodesk Maya
Integration to & evaluation in
professional workflow
Applications to 

other design domains
Summary
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Optimization-Guided Motion Editing
• Optimization is used for
enhancing manual editing
• OptiMo allows animators to
interactively control
optimization
49
Animator’s control
less
ive
ng
Interactive control
by animators
Automatic adjustment
by optimization
Yuki Koyama and Masataka Goto. OptiMo: Optimization-Guided Motion
Editing for Keyframe Character Animation. CHI 2018.
http://koyama.xyz/project/optimo/
Slides & videos available! We also plan to release our source codes!
OptiMo:
Optimization-Guided Motion Editing
for Keyframe Character Animation
Yuki Koyama & Masataka Goto
Appendix
Related Work
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Motion Editing Techniques — Automatic
54
[Witkin+88] [Merel+17]
Optimization with
space-time
constraints
Use of
learned motion
controllers
Difficult to reflect artistic
intention
➡ Lack of controllability
Resulting motions do not
have curve-based data
representation
➡ Lack of editability
OptiMo’s Features
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
We Designed 6 Features for OptiMo
56
1. Preservation of control handles [ T & E ]
2. Optimization process visualization [ T ]
3. Cost visualization [ T ]
4. Interactive regularization [ T & C ]
5. Per-Joint regularization [ C ]
6. Time-varying cost control [ C ]
Editability
Transparency
Controllability
Algorithm:
How Does Optimization Work?
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Typical Optimization Formulation
58
min
x
⇢Z
C(x, t)dt
Cost function
C(x, t)
Search parameters
x
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Parametrization (Search Space)
59
Time
Rig value
Use the control handle
parameters (that
animators otherwise
manipulate manually) as
the search parameters
of the optimization
➡ This ensures editability (and also transparency)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Cost Function: Our (Current) Choice
• Is well-established and used in computer graphics and
robotics (c.f. [Safonova+04])
• Is a summation of necessary torques (rotational forces) on
each joint
• Is useful for avoiding physically unfeasible motions
60
C(x, t) =
X
j2J
k⌧j(x, t)k2
Validation: Interview with
Professional Animators
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Comments on Editability
• Both A1 and A2 loved editability
• A1: Editability is “indispensable”
• This comment especially validates our parametrization:
• A2: It is acceptable for “the [tangent] handles to change,”
but “the keyframes (key points) should not be change” by
optimization
62
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Comments on Transparency
• Both A1 and A2 loved the visualization features
• A1: The process visualization “is very interesting”
• We observed that both A1 and A2 easily understood the
concept of optimization by seeing the visualizations
63
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Comments on Controllability
• All features on controllability were strongly appreciated
• A2: “I would be puzzled if I can’t use this”
• The interactivity of control features was appreciated
• A1: These features could make adjustment “easier” and
“less stressful”
64
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Comments on Usages in Production
• The current system is not perfect yet, but it could be useful…
• A2: For “sub-characters’ motion,” or
• A1: In “projects with only limited time”
• Both A1 and A2 got very excited about the (production-level)
quality of the fox tail animation
• A2: “It is possible to provide it by hand, but it requires much
tweaking to make it (the motion) look natural”
65
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Other Comments
• It would be nice if motion styles could be handled in the
cost function as well as physics
• A2: “Each art project has a specific style of motions” and “it
would be nice if it automates [the process of applying such
styles]”
66
Example Usage Scenarios
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Example: Stick Figure Waving His Arm
• #parameters: 78
• Rig: Forward kinematics (FK)
68
Example 1: Stick Figure Waving His Arm
Initial Naïve opt. Controlled opt.
Too robotic… The spine/elbow bend wrongly… Looks natural :)
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Example: Fox Tail
• #parameters: 27
• Rig: Forward kinematics (FK)
70
Example: Fox Tail
Inspiration:
Let’s make the swing speedier
Time-varying cost control
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Example: Music Conductor
• #parameters: 54
• Rig: Forward kinematics (FK)
and inverse kinematics (IK)
72
The next slide contains audio!
Example: Music Conductor
Example: Music Conductor
Example: Music Conductor
Example: Music Conductor
Discussions
Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018
Discussion: “One is not Enough”
78
Muscle models [Wang+12] Motion styles [Grochow+04]
Providing more options of cost functions as well as our
physics-based cost function — One is not enough!

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[CHI 2018] OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation

  • 1. OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation Yuki Koyama & Masataka Goto
  • 2. Optimization Techniques: - Powerful - Used in computer science and engineering https://en.wikipedia.org/wiki/Mathematical_optimization
  • 3. How can animators utilize optimization techniques for motion editing effectively?
  • 5.
  • 6. Background: How Do Animators Create Motions?
  • 7. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 How Do Animators Create Motions? 7 1. Keyframing 2. Curve Editing
  • 8. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 How Do Animators Create Motions? 8 1. Keyframing 2. Curve Editing Define key poses at several keyframes Adjust interpolation curves 
 (how key poses are interpolated between keyframes) frame = 4 frame = 14 … Time
  • 9. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 How Do Animators Create Motions? 9 1. Keyframing 2. Curve Editing Define key poses at several keyframes frame = 4 frame = 14 … Our Target Adjust interpolation curves 
 (how key poses are interpolated between keyframes)
  • 10. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Curve Editing is Important for Nuances 10 frame = 4 frame = 14 frame = 24 frame = 34 Even with the same keyframing, motions could be very different in nuances
  • 12. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Difficulties in Curve Editing 12 Unintuitive (indirect) effects Need to play motions every time manipulating handles Many parameters High-dimensional search task
  • 13. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Difficulties in Curve Editing 13 Unintuitive (indirect) effects Need to play motions every time manipulating handles Many parameters High-dimensional search task
  • 14. A Possible (?) Solution: 
 Naïve Optimization
  • 15. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Optimization for Full Automation? 15 Optimization can fully automate the task, 
 but results are not always satisfactory (no control…)
  • 17. Design Goals: What Should be Considered for Effective Interaction?
  • 18. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 18 ? Blackbox Original motion Optimal motion
  • 19. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 19 1. Transparent Original motion Optimal motion
  • 20. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 20 1. Transparent Original motion Optimal motion Feature: Optimization Process Visualization (for Transparency)
  • 21. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 21 1. Transparent Original motion Optimal motion Feature: Cost Visualization (for Transparency)
  • 22. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 22 1. Transparent Original motion Optimal motion
  • 23. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 23 1. Transparent 2. Controllable Original motion Optimal motion
  • 24. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 24 1. Transparent 2. Controllable Original motion Optimal motion Feature: Interactive Regularization (for Controllability)
  • 25. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 25 1. Transparent 2. Controllable Original motion Optimal motion Feature: Time-Varying Cost Control (for Controllability)
  • 26. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 26 1. Transparent 2. Controllable Original motion Optimal motion
  • 27. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 27 1. Transparent 2. Controllable … 3. Editable Manual revision allowed Original motion Optimal motion
  • 28. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 28 1. Transparent 2. Controllable … 3. Editable Manual revision allowed Original motion Optimal motion Opt. Control handles Preserved Feature: Preservation of Control Handles (for Editability)
  • 29. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 29 1. Transparent 2. Controllable … 3. Editable Manual revision allowed Original motion Optimal motion Opt. Control handles Preserved Different arrangement Different data structure Feature: Preservation of Control Handles (for Editability)
  • 30. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Three Design Goals 30 1. Transparent 2. Controllable … 3. Editable Manual revision allowed Original motion Optimal motion
  • 31. Math: How to Formulate Optimization with Controllability
  • 32. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Optimization with Controllability 32 min x ⇢Z C(x, t)dtTypical optimization
  • 33. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Optimization with Controllability 33 min x ⇢Z wcost (t)C(x, t)dt + wreg D(x, xinit ) min x ⇢Z C(x, t)dt Control by time-varying cost weight Control by regularization weight Typical optimization Controllable optimization
  • 34. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Optimization with Controllability 34 min x ⇢Z wcost (t)C(x, t)dt + wreg D(x, xinit ) min x ⇢Z C(x, t)dt Control by time-varying cost weight Control by regularization weight Adjusted in real time Typical optimization Controllable optimization
  • 36. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Example: Fox Tail • #parameters: 27 • Rig: Forward kinematics (FK) 36
  • 37. Example: Fox Tail Initial motion - Too robotic… Let’s apply the (naïve) optimization first
  • 38. Example: Fox Tail Naïve optimization - Too much changed! Let’s control it by regularization
  • 39. Example: Fox Tail Optimization with regularization - Looks good!! Inspiration: How about making the swing speedier?
  • 40. Example: Fox Tail Optimization with regularization & time-varying cost Time-varying cost weight
  • 42. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Informal Interview Goals • Validation of our approach (design goals, interactions, etc.) Participants • 2 professional animators (A1 & A2) who are familiar with 3D character animation authoring Procedure • Explain our design goals, explain our system features, and ask feedback comments (approx. 1 hour) 42
  • 43. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Results Editability • Both A1 and A2 loved editability, which was described “indispensable” (A1) Transparency • We observed that both A1 and A2 easily understood the concept of optimization by just seeing the visualizations Controllability • All features on controllability were strongly appreciated • The interactivity makes the adjustment “easier” and “less stressful” (A1) 43
  • 45. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Related Work: Motion Editing Techniques 45 [Kazi+16][Glauser+16] Tangibles [Choi+16] Sketches Principles Optimization Ours
  • 46. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Related Work: Design Interface with Optimization 46 [Koyama+14] [Umetani+14] Ours Photo color adjustment, etc. Paper airplanes Character motions [O’Donovan+15] Graphic layout
  • 47. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Future Work 47 E.g., architecture design [Kilian+17]E.g., Autodesk Maya Integration to & evaluation in professional workflow Applications to 
 other design domains
  • 49. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Optimization-Guided Motion Editing • Optimization is used for enhancing manual editing • OptiMo allows animators to interactively control optimization 49 Animator’s control less ive ng Interactive control by animators Automatic adjustment by optimization
  • 50. Yuki Koyama and Masataka Goto. OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation. CHI 2018. http://koyama.xyz/project/optimo/ Slides & videos available! We also plan to release our source codes!
  • 51. OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation Yuki Koyama & Masataka Goto
  • 54. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Motion Editing Techniques — Automatic 54 [Witkin+88] [Merel+17] Optimization with space-time constraints Use of learned motion controllers Difficult to reflect artistic intention ➡ Lack of controllability Resulting motions do not have curve-based data representation ➡ Lack of editability
  • 56. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 We Designed 6 Features for OptiMo 56 1. Preservation of control handles [ T & E ] 2. Optimization process visualization [ T ] 3. Cost visualization [ T ] 4. Interactive regularization [ T & C ] 5. Per-Joint regularization [ C ] 6. Time-varying cost control [ C ] Editability Transparency Controllability
  • 58. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Typical Optimization Formulation 58 min x ⇢Z C(x, t)dt Cost function C(x, t) Search parameters x
  • 59. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Parametrization (Search Space) 59 Time Rig value Use the control handle parameters (that animators otherwise manipulate manually) as the search parameters of the optimization ➡ This ensures editability (and also transparency)
  • 60. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Cost Function: Our (Current) Choice • Is well-established and used in computer graphics and robotics (c.f. [Safonova+04]) • Is a summation of necessary torques (rotational forces) on each joint • Is useful for avoiding physically unfeasible motions 60 C(x, t) = X j2J k⌧j(x, t)k2
  • 62. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Comments on Editability • Both A1 and A2 loved editability • A1: Editability is “indispensable” • This comment especially validates our parametrization: • A2: It is acceptable for “the [tangent] handles to change,” but “the keyframes (key points) should not be change” by optimization 62
  • 63. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Comments on Transparency • Both A1 and A2 loved the visualization features • A1: The process visualization “is very interesting” • We observed that both A1 and A2 easily understood the concept of optimization by seeing the visualizations 63
  • 64. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Comments on Controllability • All features on controllability were strongly appreciated • A2: “I would be puzzled if I can’t use this” • The interactivity of control features was appreciated • A1: These features could make adjustment “easier” and “less stressful” 64
  • 65. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Comments on Usages in Production • The current system is not perfect yet, but it could be useful… • A2: For “sub-characters’ motion,” or • A1: In “projects with only limited time” • Both A1 and A2 got very excited about the (production-level) quality of the fox tail animation • A2: “It is possible to provide it by hand, but it requires much tweaking to make it (the motion) look natural” 65
  • 66. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Other Comments • It would be nice if motion styles could be handled in the cost function as well as physics • A2: “Each art project has a specific style of motions” and “it would be nice if it automates [the process of applying such styles]” 66
  • 68. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Example: Stick Figure Waving His Arm • #parameters: 78 • Rig: Forward kinematics (FK) 68
  • 69. Example 1: Stick Figure Waving His Arm Initial Naïve opt. Controlled opt. Too robotic… The spine/elbow bend wrongly… Looks natural :)
  • 70. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Example: Fox Tail • #parameters: 27 • Rig: Forward kinematics (FK) 70
  • 71. Example: Fox Tail Inspiration: Let’s make the swing speedier Time-varying cost control
  • 72. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Example: Music Conductor • #parameters: 54 • Rig: Forward kinematics (FK) and inverse kinematics (IK) 72 The next slide contains audio!
  • 78. Yuki Koyama and Masataka Goto (AIST, Japan) | OptiMo: Optimization-Guided Motion Editing for Keyframe Character Animation | CHI 2018 Discussion: “One is not Enough” 78 Muscle models [Wang+12] Motion styles [Grochow+04] Providing more options of cost functions as well as our physics-based cost function — One is not enough!