Intelligent Tools for Creative Graphics
by Crowdsourcing
Yuki Koyama
National Institute of Industrial Science and Technology (AIST), JapanIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)1

Yuki Koyama

https://koyama.xyz/

Yuki Koyama is a researcher at National Institute of Advanced
Industrial Science and Technology (AIST), where he is amember of Media Interaction Group. He received his Ph.D.
from The University of Tokyo in 2017, advised by Takeo
Igarashi. His research fields are mainly computer graphics andhuman-computer interaction. In particular, he is interested inenhancing various design activities by employing
computational techniques such as mathematical optimization.

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)2Agenda (25min)• Introduction: How Tools Can Be Intelligent by Crowdsourcing• Basics: Crowdsourcing and Related Concepts• Formulation: Perceptual Feedback from Crowds• Intelligent Tools Case 1: Intelligent Sliders and Suggestions• Intelligent Tools Case 2: Intelligent Automatic Solver• Discussions: Other Types of IntelligenceIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

3Introduction
How Tools Can Be Intelligent by Crowdsourcing

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Parameter Tweaking is a Common Task

Photo color enhancement

GeneraZve modeling

Graphic design

Procedural designIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Parameter Tweaking is a Common Task

Task: Find the most
Photo color enhancement

GeneraZve modelingpreferable design fromthe high-dimensionalparameter space

Graphic design

Procedural designIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Parameter Tweaking with Typical Sliders
Problem:• This requires many trials and errors, and so thiscan be tedious and time-consuming
Why not automating via simple scripting?
• Preference is based on human perception, and so
automation is not trivial without some intelligenceQuestion:• How can we make tools intelligent so that they
can handle human perception?
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Parameter Tweaking with Typical Sliders
Problem:• This requires many trials and errors, and so thiscan be tedious and time-consuming
Why not automating via simple scripting?
• Preference is based on human perception, and so
automation is not trivial without some intelligenceQuestion:• How can we make tools intelligent so that they
can handle human perception?
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)8

Parameter Tweaking with Typical Sliders
Problem:• This requires many trials and errors, and so thiscan be tedious and time-consuming
Why not automating via simple scripting?
• Preference is based on human perception, and so
automation is not trivial without some intelligenceQuestion:• How can we make tools intelligent so that they
can handle human perception?
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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A Solution: Crowdsourcing
Crowdsourcing can be a software component of an
intelligent tool
• The tool can systematically query crowd workers
when necessary

Crowd workers(or crowd-generated data)

We can incorporate human intelligence into the tool
• To quantify perception-related concepts (e.g.,
preference)➡ “Crowd-powered” intelligent toolsIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)“Intelligent” tool

User

10



Typical sliders

Crowdsourcing
Typical sliders

Enhanced sliders with guidance

Crowdsourcing
Typical sliders

Enhanced sliders with guidance

Crowdsourcing
Typical sliders

Intelligent suggestions

Enhanced sliders with guidance

Crowdsourcing

Intelligent suggestions

Typical sliders“People’s choice” solverBasics
Crowdsourcing and Related Concepts

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Concept: Crowdsourcing• Jeff Howe (an author of WIRED) defined the term, crowdsourcing, in 2006
“the act of taking a job traditionally performed by a designated agent(usually an employee) and outsourcing it to an undefined, generally large
group of people in the form of an open call”• This term itself is not related to computer science or software engineering
Jeff Howe. 2006. Crowdsourcing: A Definition. https://crowdsourcing.typepad.com/cs/2006/06/crowdsourcing_a.html
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Concept: Crowdsourcing
Possible Styles• Microtask (e.g., Amazon Mechanical Turk)• Expert (e.g., Upwork)• Volunteering (e.g., open calls in citizen science projects)• … etc.
In the rest of this course, we assume the microtask-based crowdsourcing since it has
good reproducibility, stability, and scalability, and we can use it on demand.

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Concept: Human Computation• Luis von Ahn (a pioneer of human computation) [2005] described it as“a paradigm for utilizing human processing power to solve problems thatcomputers cannot yet solve”• How to obtain human processing power• Gamification (FoldIt, …)• Embedding into existing tasks (reCAPTCHA, …)• Microtask-based crowdsourcing (next slide)[von Ahn, 2005] Luis von Ahn. 2005. Human Computation. PhD thesis, Carnegie Mellon University, CMU-CS-05-193. http://reportsarchive.adm.cs.cmu.edu/anon/2005/CMU-CS-05-193.pdf
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Concept: Crowdsourced Human Computation• Consider crowd workers as intelligent processing power• Ask crowds to perform microtasks in the manner of function callsIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Concept: Crowdsourced Human Computation
Which one do you
prefer perceptually?

👍👍👍👍
👍👍👍

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)👍21

Crowdsourced Human Computation: Example

Crowds-in-the-loop algorithm

Input image

Depth map by crowds[Gingold+, TOG (2012)] Yotam Gingold, Ariel Shamir, and Daniel Cohen-Or. 2012. Micro perceptual human computation for visual tasks. ACM Trans.
Graph. 31, 5, 119:1–119:12 (2012). https://doi.org/10.1145/2231816.2231817
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)22

Crowdsourced Human Computation: Example

HP: human processor

Crowds-in-the-loop algorithm

Input image

Depth map by crowds[Gingold+, TOG (2012)] Yotam Gingold, Ariel Shamir, and Daniel Cohen-Or. 2012. Micro perceptual human computation for visual tasks. ACM Trans.
Graph. 31, 5, 119:1–119:12 (2012). https://doi.org/10.1145/2231816.2231817
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

23Formulation
Perceptual Feedback from Crowds

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Problem Definition from Mathematical Viewpoint• Suppose that we have n sliders to adjustn• Let 𝒳 = [0,1] be the search space and x ∈ 𝒳
be a set of n parameter values• Let g : 𝒳 → ℝ be a perceptual preferencefunction (= goodness function) which returns a
goodness value• We want to solve an optimization problem:

x* = argmax g(x)x∈𝒳

[Koyama+, Computational Interaction (2018)] Yuki Koyama and Takeo Igarashi. 2018. Computational Design with Crowds. In Computational
Interaction (Eds. Antti Oulasvirta, Per Ola Kristensson, Xiaojun Bi, and Andrew Howes), Oxford University Press, pp.153—184.
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

25Interacting with Perceptual Functions• Absolute assessment
should not be used:
Crowds cannot directly
answer the function value
reliably [Koyama+18]• Relative assessment
should be used:
Crowds can answer which
option is better amongtwo (or more) options

Absolute
assessment

A

B

Relativeassessment[Koyama+, Computational Interaction (2018)] Yuki Koyama and Takeo Igarashi. 2018. Computational Design with Crowds. In Computational
Interaction (Eds. A. Oulasvirta, P. O. Kristensson, X. Bi, and A. Howes), Oxford University Press, pp.153–184. https://arxiv.org/abs/2002.08657
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Interacting with Perceptual Functions• Absolute assessment
should not be used:
Crowds cannot directly
answer the function value
reliably [Koyama+18]• Relative assessment
should be used:
Crowds can answer which
option is better amongtwo (or more) options

Absolute
assessment

A

B

Relativeassessment[Koyama+, Computational Interaction (2018)] Yuki Koyama and Takeo Igarashi. 2018. Computational Design with Crowds. In Computational
Interaction (Eds. A. Oulasvirta, P. O. Kristensson, X. Bi, and A. Howes), Oxford University Press, pp.153–184. https://arxiv.org/abs/2002.08657
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Intelligent Tools Case 1Intelligent Suggestions and Sliders[Koyama+, UIST 2014] Yuki Koyama, Daisuke Sakamoto, and Takeo Igarashi. 2014. Crowd-powered parameter analysis for visual design exploration.
In Proc. UIST '14. pp.65–74. https://doi.org/10.1145/2642918.2647386
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5BSHFU1BSBNFUFST

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5BSHFU1BSBNFUFST%FTJHO4QBDF)VNBO1SPDFTTPSTPreference data generation [pairwise comparison](c.f.,
comparisons,USD,min) )VNBO1SPDFTTPST
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5BSHFU1BSBNFUFST%FTJHO4QBDF)VNBO1SPDFTTPST

/PU(PPE

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5BSHFU1BSBNFUFST%FTJHO4QBDF(PPE(PPEOFTT'VODUJPO)VNBO1SPDFTTPSTIntelligent Tools by Goodness Function Estimation
Not Good

NotGood
Good

Good

Visualization
Visualization

Interactive Interactive
Optimization
Optimization
User’s EditUser’s Edit
Parameter SpaceParameter SpaceSuggested Suggested
Designs Designs

Goodness-aware suggestions for ideation Goodness-aware sliders for guided exploration

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)38

1. Goodness-Aware Suggestions

Purely random sampling (unaware ofgoodness) would generate many
unreasonable suggestions that are not
worth providing to the userIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)39

1. Goodness-Aware Suggestions

Purely random sampling (unaware ofgoodness) would generate many
unreasonable suggestions that are not
worth providing to the user

Goodness-aware sampling (biased
toward the “good” region) would
generate reasonable suggestions that areworth providing to the userIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)40

2. Goodness-Aware Sliders■ Visualization of the crowds’ preference■ Interactive optimization of slider values

Photo Enhancement ( D)

Camera & Light Placement ( D)Material Appearance ( D)

Facial Expression (D)

Intelligent Tools Case 2Intelligent Automatic Solver[Koyama+, SIGGRAPH 2017] Yuki Koyama, Issei Sato, Daisuke Sakamoto, and Takeo Igarashi. 2017. Sequential Line Search for Efficient Visual Design
Optimization by Crowds. ACM Trans. Graph. 36, 4, pp.48:1–48:11 (2017). https://doi.org/10.1145/3072959.3073598
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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“Crowdsource” buttonin the tool

“People’s Choice”
optimal slider values

Crowd-powered optimization[Koyama+, SIGGRAPH 2017] Yuki Koyama, Issei Sato, Daisuke Sakamoto, and Takeo Igarashi. 2017. Sequential Line Search for Efficient Visual Design
Optimization by Crowds. ACM Trans. Graph. 36, 4, pp.48:1–48:11 (2017). https://doi.org/10.1145/3072959.3073598

[Koyama+, SIGGRAPH 2017] Yuki Koyama, Issei Sato, Daisuke Sakamoto, and Takeo Igarashi. 2017. Sequential Line Search for Efficient Visual Design
Optimization by Crowds. ACM Trans. Graph. 36, 4, pp.48:1–48:11 (2017). https://doi.org/10.1145/3072959.3073598

“Relative Assessment” Microtask Design
Task: Choose the image thatlooks better

Basic: Pairwise comparison(e.g., [Koyama+, UIST])Task: Adjust the slider so thatthe image looks the best

Advanced: Single-slider manipulation(provides much richer information)➡ Faster convergenceIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Web interface for crowdsourcing

Algorithm: Sequential Line Search
A human-in-the-loop Bayesian optimization

Please refer to [Koyama+, SIGGRAPH 2017] for the mathematical details[Koyama+, SIGGRAPH 2017] Yuki Koyama, Issei Sato, Daisuke Sakamoto, and Takeo Igarashi. 2017. Sequential Line Search for Efficient Visual Design
Optimization by Crowds. ACM Trans. Graph. 36, 4, pp.48:1–48:11 (2017). https://doi.org/10.1145/3072959.3073598

Applications #Photo Color Enhancement ( D)For each photo, it runs

iterations, cost .

USD in total, and took

min in average

For each photo, it runs

iterations, cost .

USD in total, and took

min in averageReplayFor each photo, it runs

iterations, cost .

USD in total, and took

min in average

For each photo, it runs

iterations, cost .

USD in total, and took

min in averageEvaluation: Crowdsourced Voting
Q. Which one do you like?
Original

By Crowds

By PhotoshopIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

By Lightroom

55

Crowds

Crowds

Crowds

Q. Which one do you like?
Original

By Crowds

By Photoshop

By Lightroom👍➡ As they are the “people’s choice” enhancements, people preferred themIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

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Applications #Material Appearance ( D / D)Usage Scenario #Material Appearance from Reference PhotographUsage Scenario #Material Appearance from Text Instruction

Discussions
Other Types of IntelligenceIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

65Types of Intelligence Enabled by Crowdsourcing• General preference• Perceptual similarity• [Koyama+, UIST 2014]• [Garces+, SIGGRAPH 2014],• [Koyama+, SIGGRAPH 2017]• [O’Donovan+, SIGGRAPH 2014]• Perceptual compatibility• [Secord+, TOG (2012)]• [Zhu+, SA 2014]• [Laursen+, PG Short 2016]• Semantic attributes• [Liu+, SIGGRAPH 2015]• [Yumer+, SIGGRAPH 2015]• … etc.

• [O’Donovan+, SIGGRAPH 2014]• [Chaudhuri+, UIST 2013]

Please note that this list is not exhaustiveIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

66Types of Intelligence Enabled by Crowdsourcing• General preference• Perceptual similarity• [Koyama+, UIST 2014]• [Garces+, SIGGRAPH 2014],• [Koyama+, SIGGRAPH 2017]• [O’Donovan+, SIGGRAPH 2014]• Perceptual compatibility• [Secord+, TOG (2012)]• [Zhu+, SA 2014]• [Laursen+, PG Short 2016]• Semantic attributes• [Liu+, SIGGRAPH 2015]• [Yumer+, SIGGRAPH 2015]• … etc.

• [O’Donovan+, SIGGRAPH 2014]• [Chaudhuri+, UIST 2013]

Please note that this list is not exhaustiveIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

67Types of Intelligence [1/4]: General Preference
E.g., by learning crowds’ preference in portrait expressions, the tool can intelligently
select best expressions from a long video or a large collection of photographs[Zhu+, SA 2014] Jun-Yan Zhu, Aseem Agarwala, Alexei A. Efros, Eli Shechtman, and Jue Wang. 2014. Mirror mirror: crowdsourcing better portraits. ACM
Trans. Graph. 33, 6, pp.234:1–234:12 (2014). https://doi.org/10.1145/2661229.2661287
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

68Types of Intelligence [2/4]: Semantic Attributes• Human-understandable concepts (such as “modern”, “strong”, etc.)• Based on semantic attributes, users can intuitively explore different visual options[Yumer+, SIGGRAPH 2015] Mehmet Ersin Yumer, Siddhartha Chaudhuri, Jessica K. Hodgins, and Levent Burak Kara. 2015. Semantic shape editing using
deformation handles. ACM Trans. Graph. 34, 4, pp.86:1–86:12 (2015). https://doi.org/10.1145/2766908
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

69Types of Intelligence [3/4]: Perceptual Similarity
E.g., crowdsourcing can be used to measure or estimate perceptual similarity
between illustrations, which enables an intelligent search tool

[Garces+, SIGGRAPH 2014] Elena Garces, Aseem Agarwala, Diego Gutierrez, and Aaron Hertzmann. 2014. A similarity measure for illustration style. ACM
Trans. Graph. 33, 4, 93:1–93:9 (2014). https://doi.org/10.1145/2601097.2601131
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Types of Intelligence [4/4]: Perceptual Compatibility• Compatibility: how well multiple
objects go together• E.g., by estimating perceptual
compatibility between 3D model
assets, a scene assembly tool cansuggest reasonable variations[Liu+, SIGGRAPH 2015] Tianqiang Liu, Aaron Hertzmann, Wilmot Li, and Thomas Funkhouser. 2015. Style compatibility for 3D furniture models. ACM
Trans. Graph. 34, 4, pp.85:1–85:9 (2015). https://doi.org/10.1145/2766898
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Beyond Parameter Tweaking

Crowd-powered tools can generate structured
perceptual feedbacks for the on-going design,in an on-demand manner[Xu+, CSCW 2014] Anbang Xu, Shih-Wen Huang, and Brian Bailey. 2014. Voyant: generating structured feedback on visual designs using a crowd of nonexperts. In Proc. CSCW ’14. pp.1433–1444. https://doi.org/10.1145/2531602.2531604
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)72Another Approach to Incorporate Human Intelligence
Build tools that involve the user (instead of crowds) in their routine loop
• The crowds-in-the-loop Bayesian optimization algorithm [Koyama+, SIGGRAPH 2017] wasextended for building a new user-in-the-loop optimization tool [Koyama+, SIGGRAPH 2020]
Sequential Gallery

Initial…

Optimized…

[Koyama+, SIGGRAPH 2020] Yuki Koyama, Issei Sato, and Masataka Goto. 2020. Sequential Gallery for Interactive Visual Design Optimization. ACM Trans.
Graph. 39, 4, pp.88:1–88:12 (2020). https://doi.org/10.1145/3386569.3392444
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)73Another Approach to Incorporate Human Intelligence
Build tools that involve the user (instead of crowds) in their routine loop
• The crowds-in-the-loop Bayesian optimization algorithm [Koyama+, SIGGRAPH 2017] wasextended for building a new user-in-the-loop optimization tool [Koyama+, SIGGRAPH 2020]
Sequential Gallery

Initial…

Optimized…

[Koyama+, SIGGRAPH 2020] Yuki Koyama, Issei Sato, and Masataka Goto. 2020. Sequential Gallery for Interactive Visual Design Optimization. ACM Trans.
Graph. 39, 4, pp.88:1–88:12 (2020). https://doi.org/10.1145/3386569.3392444
Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)74Summary
Intelligent Tools for Creative Graphics by Crowdsourcing

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)75Summary
Tools can be more intelligent by crowdsourcing• Crowdsourcing enables tools to quantify
perception-related concepts• E.g., preference, semantic attributes, etc.
• Crowd-powered tools can offer functions for
guided exploration, including …
• Enhanced sliders with guidance• Intelligent suggestions• “People’s choice” solverIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

76Summary
Tools can be more intelligent by crowdsourcing• Crowdsourcing enables tools to quantify
perception-related concepts• E.g., preference, semantic attributes, etc.
• Crowd-powered tools can offer functions for
guided exploration, including …
• Enhanced sliders with guidance• Intelligent suggestions• “People’s choice” solverIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

Crowd workers(or crowd-generated data)“Intelligent” tool

User
77

Summary
Tools can be more intelligent by crowdsourcing• Crowdsourcing enables tools to quantify
perception-related concepts• E.g., preference, semantic attributes, etc.
• Crowd-powered tools can offer functions for
guided exploration, including …
• Enhanced sliders with guidance• Intelligent suggestions• “People’s choice” solverIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

Enhanced sliders withguidance

Intelligent
suggestions“People’s choice”
solver78

References• [Garces+, SIGGRAPH 2014] Elena Garces, Aseem Agarwala, Diego Gutierrez, andAaron Hertzmann. 2014. A similarity measure for illustration style. ACM Trans.
Graph. 33, 4, 93:1–93:9 (2014). https://doi.org/10.1145/2601097.2601131• [Gingold+, TOG (2012)] Yotam Gingold, Ariel Shamir, and Daniel Cohen-Or.
2012. Micro perceptual human computation for visual tasks. ACM Trans. Graph.
31, 5, 119:1–119:12 (2012). https://doi.org/10.1145/2231816.2231817• [Koyama+, UIST 2014] Yuki Koyama, Daisuke Sakamoto, and Takeo Igarashi.
2014. Crowd-powered parameter analysis for visual design exploration. In Proc.
UIST '14. pp.65–74. https://doi.org/10.1145/2642918.2647386• [Koyama+, SIGGRAPH 2017] Yuki Koyama, Issei Sato, Daisuke Sakamoto,and Takeo Igarashi. 2017. Sequential Line Search for Efficient Visual Design
Optimization by Crowds. ACM Trans. Graph. 36, 4, pp.48:1–48:11 (2017).
https://doi.org/10.1145/3072959.3073598• [Koyama+, Computational Interaction (2018)] Yuki Koyama and Takeo
Igarashi. 2018. Computational Design with Crowds. In Computational
Interaction (Eds. Antti Oulasvirta, Per Ola Kristensson, Xiaojun Bi, and Andrew
Howes), Oxford University Press, pp.153–184. https://arxiv.org/abs/2002.08657• [Koyama+, SIGGRAPH 2020] Yuki Koyama, Issei Sato, and Masataka
Goto. 2020. Sequential Gallery for Interactive Visual Design Optimization. ACM

Trans. Graph. 39, 4, pp.88:1–88:12 (2020). https://doi.org/
10.1145/3386569.3392444• [Liu+, SIGGRAPH 2015] Tianqiang Liu, Aaron Hertzmann, Wilmot Li, and Thomas
Funkhouser. 2015. Style compatibility for 3D furniture models. ACM Trans.
Graph. 34, 4, pp.85:1–85:9 (2015). https://doi.org/10.1145/2766898• [von Ahn, 2005] Luis von Ahn. 2005. Human Computation. PhD thesis, Carnegie
Mellon University, CMU-CS-05-193. http://reports-archive.adm.cs.cmu.edu/
anon/2005/CMU-CS-05-193.pdf• [Xu+, CSCW 2014] Anbang Xu, Shih-Wen Huang, and Brian Bailey. 2014. Voyant:generating structured feedback on visual designs using a crowd of non-experts.
In Proc. CSCW ’14. pp.1433–1444. https://doi.org/10.1145/2531602.2531604• [Yumer+, SIGGRAPH 2015] Mehmet Ersin Yumer, Siddhartha Chaudhuri, Jessica
K. Hodgins, and Levent Burak Kara. 2015. Semantic shape editing using
deformation handles. ACM Trans. Graph. 34, 4, pp.86:1–86:12 (2015). https://doi.org/10.1145/2766908• [Zhu+, SA 2014] Jun-Yan Zhu, Aseem Agarwala, Alexei A. Efros, Eli Shechtman,
and Jue Wang. 2014. Mirror mirror: crowdsourcing better portraits. ACM Trans.
Graph. 33, 6, pp.234:1–234:12 (2014). https://doi.org/
10.1145/2661229.2661287

Intelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

79Intelligent Tools for Creative Graphics
by Crowdsourcing
Yuki Koyama
National Institute of Industrial Science and Technology (AIST), JapanIntelligent Tools for Creative Graphics (SIGGRAPH 2020 Course)

80