Color is a perceptual phenomenon that can be explored through psychometrics and modeling of attribute correlates. Color is also a cognitive phenomenon that can be researched through color naming and categorization. We begin with a review of previous research, with an emphasis on the challenges and applications of this work. Building on a large unconstrained color naming corpus collected online from over 4,000 volunteers we demonstrate the long-tail of color naming and derive an online color tool based on the thesaurus model of synonyms and antonyms.
To further improve the quality and quantity of the underlying naming corpus, we introduce two novel feedback mechanisms to the Italian version of the online color thesaurus: instance based harvesting of missing names and optional user ranking of included names. This allows a more efficient creation of a higher quality color naming corpus.
NID - pgdpd application form for 2013 - download here, Entrance exam is on 19th January 2013. Last date to fill up the application form is 2nd November, 2012. Post graduate applicants applying for 2 streams are required to fill up 2 separate application forms.
NID - pgdpd application form for 2013 - download here, Entrance exam is on 19th January 2013. Last date to fill up the application form is 2nd November, 2012. Post graduate applicants applying for 2 streams are required to fill up 2 separate application forms.
Integrating Row Covers & Soil Amendments for Organic Cucumber Production; Gardening Guidebook for Iowa ~ Iowa State University~ For more information, Please see websites below:
`
Organic Edible Schoolyards & Gardening with Children =
http://scribd.com/doc/239851214 ~
`
Double Food Production from your School Garden with Organic Tech =
http://scribd.com/doc/239851079 ~
`
Free School Gardening Art Posters =
http://scribd.com/doc/239851159 ~
`
Increase Food Production with Companion Planting in your School Garden =
http://scribd.com/doc/239851159 ~
`
Healthy Foods Dramatically Improves Student Academic Success =
http://scribd.com/doc/239851348 ~
`
City Chickens for your Organic School Garden =
http://scribd.com/doc/239850440 ~
`
Huerto Ecológico, Tecnologías Sostenibles, Agricultura Organica
http://scribd.com/doc/239850233
`
Simple Square Foot Gardening for Schools - Teacher Guide =
http://scribd.com/doc/239851110
Integrating Row Covers & Soil Amendments for Organic Cucumber Production; Gardening Guidebook for Iowa ~ Iowa State University~ For more information, Please see websites below:
`
Organic Edible Schoolyards & Gardening with Children =
http://scribd.com/doc/239851214 ~
`
Double Food Production from your School Garden with Organic Tech =
http://scribd.com/doc/239851079 ~
`
Free School Gardening Art Posters =
http://scribd.com/doc/239851159 ~
`
Increase Food Production with Companion Planting in your School Garden =
http://scribd.com/doc/239851159 ~
`
Healthy Foods Dramatically Improves Student Academic Success =
http://scribd.com/doc/239851348 ~
`
City Chickens for your Organic School Garden =
http://scribd.com/doc/239850440 ~
`
Huerto Ecológico, Tecnologías Sostenibles, Agricultura Organica
http://scribd.com/doc/239850233
`
Simple Square Foot Gardening for Schools - Teacher Guide =
http://scribd.com/doc/239851110
There is a very long tradition in designing color palettes for various applications. Although color palettes have been influenced by the available colorants, starting with the advent of aniline dyes there have been few physical limits on the choice of individual colors. This abundance of choices exacerbates the problem of limiting the number of colors in a palette.
The traditional solution is that of "color forecasting." Color consultants assess the sentiment or affective state of a target customer class and compare it with new colorants offered by the industry. They assemble a limited color palette, name the colors according to the sentiment, and publish their result.
The color forecasting business is very labor intensive and difficult, thus for years computer engineers have tried to come up with algorithms to design harmonious color palettes, alas with little commercial success. Contrary to the auditory sense, there is no known physiological mechanism sustaining harmony and the term "harmonious" just has the informal meaning of "going well together."
We argue that the intellectual flaw resides in the belief that a masterful individual can devise a "perfect methodology" that the engineer can then reduce to practice in a computer program. We suggest that the correct approach is to consider color forecasting as an act of distillation, where a palette is digested from the sentiment of a very large number of people. We describe how this approach can be reduced to an algorithm by replacing the subjective process with a data analytic process.
As an increasing portion of manuscripts submitted to American journals is from Asian scientists, increasing a journal impact factor is becoming more critical
The enormous possibilities and widespread connectivity offered by the Internet and the World Wide Web has spawned multiple ways of exchanging and communicating color images. The Internet is an evolving communication system, where uses, technologies, and applications are continuously introduced by a plethora of players. Its functionality, reliability, scaling properties, and performance limits are largely unknown—albeit they span wide gamuts from optic fiber to wireless connections and from game consoles to palmtop devices, etc. To be successful in Internet imaging, users and developers must design systems in a top-down approach. The goal of this tutorial is to sort out the available standard methods so that attendees will become familiar with the different possibilities for Internet imaging; the trade-offs, issues and dependencies of each; how and when each is used; and their system implications. To this end, we systematically present the standard methods for color encoding, image compression, file formatting, protocols, and applications.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
By Design, not by Accident - Agile Venture Bolzano 2024
Cognitive Aspects of Color
1. Introduction
Previous Work
Our Results & Contribution
Summary
Cognitive Aspects of Color
Aspetti cognitivi del colore
G. Beretta N. Moroney
Print Production Automation Lab
Hewlett-Packard Laboratories
Palo Alto, California
IVa Conferenza Nazionale del Gruppo del Colore
¯
Como, 18 settembre 2008
Beretta, Moroney Cognitive Aspects of Color
2. Introduction
Previous Work
Our Results & Contribution
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
3. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
4. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Emerging Display Technologies
Beretta, Moroney Cognitive Aspects of Color
5. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Today’s Nomadic Road Warrior Works Wherever
Beretta, Moroney Cognitive Aspects of Color
6. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Color Management Is Just Expected to Work
Beretta, Moroney Cognitive Aspects of Color
7. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Color Integrity
At the 1997 panel discussion on color fidelity vs. color integrity
at the Color Imaging Conference in Scottsdale we had argued:
Color fidelity cannot be achieved in consumer applications
like Internet shopping
A color never comes alone: it is part of a palette
Color fidelity is not necessary if color integrity is
maintained
1 Foveal colors should not cross name boundaries
2 The error vectors should have a uniform flux
Distortions are unavoidable, we need to control them
Beretta, Moroney Cognitive Aspects of Color
8. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Naming of Colors
In real life, the names of colors are often less important than
the names of colors of objects
Example
Delk & Fillenbaum experiment (1965)
Beretta, Moroney Cognitive Aspects of Color
9. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
More Applications of Color Naming
Once we have facilities for processing color by name, we can
find more applications:
Better user experience in GUIs
Automatic nudging of text and logo colors for readibility in
variable data printing
Gamut mapping for HDR and wide gamut displays
Culture-independent preferred color rendering
Thematic rendering
Beretta, Moroney Cognitive Aspects of Color
10. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
11. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Metric Color Discrimination
Beretta, Moroney Cognitive Aspects of Color
12. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Color Communication
stimulus detectors early mechanisms pictorial register
color
edges
contour
motion
depth
…
context parameters
chroma
etc.
hue
Color lexicon lightness
chroma internal
etc.
color space
amber hue
lightness
action color name apparent color
representation
Beretta, Moroney Cognitive Aspects of Color
13. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Color Naming Constraints
1 Physiological basis of color perception
2 General color cognition
basic vs. derived color categories
role of prototypes
formatting of internal representation
3 Color communication
sharable knowledge about the world
metaphorical names
semantic and syntactic constraints
Result: an observer can discriminate more efficiently between a
pair of colors straddling a category boundary than between a
pair in the same category
Beretta, Moroney Cognitive Aspects of Color
14. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Categorical Color Discrimination
Beretta, Moroney Cognitive Aspects of Color
15. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
16. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Development of Color Naming
Color naming is acquired, not genetic
socio-economic status (SES)
Occurs late in child’s development, but age is decreasing
with increase of technology
1900: basic four colors @ 8 years
1950: @ 5 years of age
Beretta, Moroney Cognitive Aspects of Color
17. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
Color Ontogeny of Languages
Brent Berlin and Paul Kay, University of Berkeley, 1969
The physiology underlying even the unique hues is
unknown
There is no natural categorization
orange
and/or
green yellow
white pink
and red blue brown and/or
black purple
and/or
yellow green
gray
I II III IV V VI VII
Beretta, Moroney Cognitive Aspects of Color
18. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
The Structure of Color Naming Spaces
1 What is the set of color names?
2 Where are the boundaries for synonyms?
Without a natural categorization, it is not clear where the
boundary for synonyms are
An important problem in avionics
3 How are the color names categorized algorithmically?
v’
white yellow
1. 1. 1.
.98 .92 .65 .53
.73 87 .91 orange
.55 green 1. .99 .98
.97 .88 .62
.87 .71.53
.75.88.96
.59.73 .74.57 .98 .98.96
.97 .91 .94 .33 .45 .93
.84 .66 .5 .46 A .51 .58.54 .63
.59.52 .5
.44 .31.49.63
.71 .71 .68 .78.81 .63
.7 .44 .47.52
.41.35.56
.47 .33.39.61 red
.57.56 .44 .61.61.52
B
.33 .45.56 .56 .53.53
.47.47
.43.32.46.56
aqua .77.63.38.39.56C E D
.64.53.35
.68 .76 .74.75
.58 peach
.45 .53 .7 .8
.82.65.36.45 .85.87.82.74
.45.48 .3
.52.74.81
.69.42 .36 .87 .91.89.86
.47.48.28
.33.57.69
.53.64 .5 .83.92.88 .87
.38.37.48.44
gray .62.75 .57 .7 .82.86
.53.35.56.56
.47 .56.68
.88 pink
.74.82 .53 .54 .72.74
.67 .77.59
.35 .48.51.63
.9 .84 .48
.7 .83 .8
.72.65 .5
.92.89.53
.82.92 .9 .75.69
.98 .9 .52
.83.93 .89.81
purple
blue .98 .9 .53 .83.94.92
.97 .9 .52.91
.95
.25 A = CIE Standard Illuminant A
.96.91 .6 .84
B = CIE Standard Illuminant B
.97.92.63
C = CIE Standard Illuminant C
.97.94 D = CIE Standard Illuminant D65
E = equal-energy point
.97
u’
.15
.05 .15 .25 .35 .45
David L. Post, 1988
Beretta, Moroney Cognitive Aspects of Color
19. Introduction
Broad Problem Description
Previous Work
Specific Problem Description
Our Results & Contribution
Categorical Perception
Summary
What is A Color Thesaurus?
Definition
A thesaurus is a compilation of synonyms (and antonyms) with
etymological and semantical information as well as examples to
disambiguate the synonyms
There is a number of dictionaries of color names
In 1955 Kelly and Judd produced an early color thesaurus
In 2007 Nathan Moroney created an online thesaurus of
color names
based on an earlier online color naming experiment
Beretta, Moroney Cognitive Aspects of Color
20. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
21. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
The ISCC–NBS Method of Designating Colors and A
Dictionary of Color Names
Kenneth L. Kelly & Deane B. Judd, 1955
Names from over a dozen compilations in use in the USA;
uniformity in Munsell space
1933 recommendations by I.H. Godlove + scheme of hue
modifiers + heuristics
Munsell Value
black dark gray medium gray light gray white
–ish black dark –ish gray –ish gray light –ish gray –ish white
pale
dark
blackish grayish or very pale
grayish
light grayish
very dark dark moderate light very light
Munsell Chroma
very deep deep strong brilliant
vivid
Beretta, Moroney Cognitive Aspects of Color
22. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Coloroid Color Names
Antal Nemcsics, 1993
Historical pigment names; process and structure not
documented; 70’000 observers
Structure hierarchy: 7 domains, 76 primary colors
Several errors and inconsistencies
broken warm white A = 20
cement grey Roman ochre Pompeian yellow
100
90
80
70
60
50 Indian orange
V
40 orange ochre
30 Arsigont
20 brown beige
10
Anatolian brown
0
0 10 20 30 40 50 60 70 80 90 100
T
Beretta, Moroney Cognitive Aspects of Color
23. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
24. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Color Names for Avionics
David L. Post and collaborators, 1985–1989
Start with 12-name vocabulary (basic terms + peach)
Psychophysics; present 210 stimuli (uniform in UCS) on
various backgrounds under various illuminants
Boundaries enclose areas within which the modal
color-name response corresponds with the color name
Probability of obtaining the modal color-name response
v’
white yellow
1. 1. 1.
.98 .92 .65 .53
.73 87 .91.87 orange
.55 green1. .99 .98
.97 .88 .62
.71.53 .75.88
.59.73 .74.57 .96.98 .98.96
.97 .91 .94 .33 .45.51 .93
.84 .66 .5 .46.44 A .58.54 .63.59
.52 .5
.31.49.63
.71 .71 .68 .78.81 .63
.7 .44 .47.52
.41.35.56
.47.33.39.61 red
.57.56 .44 .61.61.52
B
.33 .45.56 .56 .53.53
.47.47
.43.32.46.56
aqua .77.63.38.39.56C E D
.64.53.35
.68 .76 .74.75
.58 peach
.45 .53 .7 .8
.82.65.36.45 .85.87.82.74
.45.48 .3
.52.74.81.87
.69.42 .36 .91.89.86
.47.48.28
.33.57.69.83
.53.64 .5 .92.88 .87
.38.37.48.44
gray .62.75 .57 .7 .82.86
.53.35.56.56
.47 .56.68
.88 pink
.74.82 .53 .54.67 .72.74
.77.59 .48
.35 .9 .84 .48
.51.63
.7 .83 .8
.72.65 .5
.92.89.53
.82.92 .9 .75.69
.98 .9 .52
.83.93 .89.81
purple
blue .98 .9 .53 .83.94.92
.97 .9 .52.91
.95
.25 A = CIE Standard Illuminant A
.96.91 .6
.84
B = CIE Standard Illuminant B
.97.92.63
C = CIE Standard Illuminant C
.97.94 D = CIE Standard Illuminant D65
E = equal-energy point
.97
u’
.15
.05 .15 .25 .35 .45
David L. Post, 1988
Beretta, Moroney Cognitive Aspects of Color
25. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Influence of Culture on Color Naming
Heinrich Zollinger, ca. 1975
What is the link between the neurobiology of color vision
and color naming (embodyment)?
Subjects native speakers in:
chemistry students in German, French, English, Hebrew,
Japanese
art students in German, Hebrew
Japanese children
analphabets in Kekchi, Misquito
Tasks:
1 list minimally necessary color names
2 list supplementary color names
3 total must be 12
4 name 117 Munsell chips
Beretta, Moroney Cognitive Aspects of Color
26. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Frequency of Occurrence
Chemistry students
Häufigkeit
ETH-Zürich grün
60% blau violett
gelb
40% rotorange
rot
20% rosa
braun
purpur
5R 5YR 5Y 5GY 5G 5BG 5B 5PB 5P 5RP
80% TKD-
60%
40%
20%
5R 5YR 5Y 5GY 5G 5BG 5B 5PB 5P 5RP
Beretta, Moroney Cognitive Aspects of Color
27. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Robotic Agent Naming Colors
Johan Lammens, 1994
Beretta, Moroney Cognitive Aspects of Color
28. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
29. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Number of Color Categories
Berlin & Kay: 11 basic terms
white, black, red green yellow, blue, brown, orange, pink,
purple, grey
ISCC–NBS: 267 categories
Nemcsics: 76 primary colors
Boynton & Olson: 15 nonbasic terms are frequently used
tan, peach, olive, lavender, violet, lime, salmon, indigo,
cyan, cream, magenta, turquoise, chartreuse, rust, maroon
11 + 15 = 26
2 uninformed subjects were presented twice the 424 OSA
patches and asked how many colors they saw
one subject estimated 30, the other 80
11 is too low a number to categorize colors
Beretta, Moroney Cognitive Aspects of Color
30. Introduction
Attempts to Compile Thesauri
Previous Work
Extensions of the Basic Color Terms
Our Results & Contribution
Summary
Summary
Limitations of These Solutions
Only ISCC–NBS has a bona fide thesaurus
266 color categories with annotated synonyms
Even with 7,500 color names, the dictionary is very limited
a snapshot in time (1955)
mostly government and industry related
only in English
It is not clear how many categories there are
These limitations make it less useful
Beretta, Moroney Cognitive Aspects of Color
31. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
32. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Research Constraints
We are interested in the names of color patches
Not in free lists of color names
Not in color object names
Not in the evolution of color names
carta zucchero
102, 140, 204; #668ccc; very rare.
azzurro, indaco
azzurro scuro, ciano.
ant. maroone chiaro, ocra.
celeste orange
and/or
54, 176, 239; #36b0ef; rare.
green yellow
white pink
and red blue brown and/or
ciano, azzurro
black purple
and/or
yellow green
cyan, carta zucchero.
gray
ant. arancio, arancione. I II III IV V VI VII
Beretta, Moroney Cognitive Aspects of Color
33. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Goal
1 Large dictionary
extensive, through crowd-sourcing
evolves through time
not limited to one language
2 Number of synonym categories 12
decided though crowd-sourcing
not 266 like in ISCC–NBS thesaurus
. . . or 26, or 30, or 80. . .
3 Algorithm for determining categories
explicitly ask user for a specific and a general name
construct separate categorizations for each
explore boundary-finding algorithms
Beretta, Moroney Cognitive Aspects of Color
34. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Color Naming Experiment
Beretta, Moroney Cognitive Aspects of Color
35. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
36. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
The Color Thesaurus in English
The ephemerality is built in!
http://www.hpl.hp.com/personal/Nathan_Moroney/
color-thesaurus.html
Beretta, Moroney Cognitive Aspects of Color
37. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Color Zeitgeist
Can easily derive secondary tools
Tag cloud visualization of the color name queries
Example
Beretta, Moroney Cognitive Aspects of Color
38. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Italian Color Thesaurus
Beretta, Moroney Cognitive Aspects of Color
39. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Qualifying the Corpus
Problems:
we observed about
5% disruptive
participants in the
experiment
variability of rarely
used names
Solution is to collect
explicit feedback on the
global statistics from
each participant
More efficient than
recruiting domain
specialists
Beretta, Moroney Cognitive Aspects of Color
40. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Expanding the Corpus
Problem: Insufficient data in non-English corpora
Solutions:
1 brute force: adding a hundred names require tens of
thousands of participants
because of redundancy (long tail distribution) this is very
inefficient
when a name is missing, the cost for completing the corpus
is high
2 targeted harvesting: get participants to find sparse
regions. . .
3 . . . and submit relevant data
Beretta, Moroney Cognitive Aspects of Color
41. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Contributed Name Distribution
2000 green
blue
light blue
lavender
grass green
tan
khaki
dark brown
cornflower
cream
purple gray yellow green dark purple red orange
pink navy blue navy moss green dark red
red maroon peach burnt orange chocolate
1600 black
lime green
lime
dark blue
burgundy
salmon
spring green
pea green
crimson
coral
brown dark green light purple baby blue apple green
magenta lilac rose kelly green eggplant
violet olive gold dark pink goldenrod
sky blue olive green plum rust medium blue
1200 orange
yellow
cyan
periwinkle
brick red
beige
blue green
fluorescent green
ocean blue
leaf green
teal mint green mustard sage bright purple
light green bright green white hunter green grape
fuchsia mauve indigo pale green light yellow
800 turquoise
aqua
sea green
hot pink
bright blue
chartreuse
blue gray
cobalt
emerald
jade
royal blue neon green light brown midnight blue ochre
forest seafoam aquamarine light pink army green
brick
400
0 gre r m y t l m l p s g p r b b k b k fl b c c e l e b
en ed agen ellow urquo ight b aroo ilac eriwi ea gr rass g each ose eige right haki urnt elly g uores lue g ornflo hocol ggpla eaf gr mera rick
ta ise lue n nkl een re blu ora ree ce ray we ate nt ee ld
e en e nge n nt g r n
ree
n
Beretta, Moroney Cognitive Aspects of Color
42. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Expanding the Corpus
Beretta, Moroney Cognitive Aspects of Color
43. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
44. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Limitations of the First Experiments
We have solved:
how can we screen out bogus data?
how do we get scalability?
how can we make the experiments more collaborative?
Remaining problem:
the categorization lacks fixed boundaries
synonyms are formed ad hoc by searching for the color
names with the smallest CIECAM02 color difference
∗
greater than 5∆E02,C
Beretta, Moroney Cognitive Aspects of Color
45. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Planned Extensions
Algorithm for determining categories
explicitly ask user for a specific and a general name
construct separate categorizations for each
explore boundary-finding algorithms
Beretta, Moroney Cognitive Aspects of Color
46. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
The Density of Color Names
g
blue green
grey white
yellow
purple brown
pink
red orange
j
Beretta, Moroney Cognitive Aspects of Color
47. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Outline
1 Introduction
New Challenges in Color Management
Lexical Color
Color Naming
2 Previous Work
Attempts to Compile Thesauri
Extensions of the Basic Color Terms
Summary
3 Our Results & Contribution
Color Naming on the Web
Tools Leveraging the Corpus
Work in Progress
Results So Far
Beretta, Moroney Cognitive Aspects of Color
48. Introduction Color Naming on the Web
Previous Work Tools Leveraging the Corpus
Our Results & Contribution Work in Progress
Summary Results So Far
Statistics
120’760 synonyms served from September 2007 through
August 2008
Syndicated by
Core Design 77
http://www.core77.com/blog/object_culture/online_color_thesaurus_7966.asp
Aubrey Jaffer
http://people.csail.mit.edu/jaffer/Color/Dictionaries
MagCloud reference magazine, available from
http://magcloud.com/browse/Issue/2344
Beretta, Moroney Cognitive Aspects of Color
49. Introduction
Previous Work
Our Results & Contribution
Summary
Summary
There are applications requiring a color thesaurus
Current solutions are not adequate
We have a promising early solution that scales well
Outlook
Research is required to tile the color space and build a true
thesaurus
Eventually, the tool should be so robust we can run it for a
language none of us speaks
Beretta, Moroney Cognitive Aspects of Color
50. Introduction
Previous Work
Our Results & Contribution
Summary
Acknowledgments
We are indebted to Prof. Lucia R. Ronchi of the Fondazione
Giorgio Ronchi in Florence for many fruitful discussions and for
compiling the book on Color and Language
Beretta, Moroney Cognitive Aspects of Color
51. Introduction
Previous Work
Our Results & Contribution
Summary
Questions and Discussion
mailto:giordano.beretta@hp.com
http://www.hp.com/blogs/mostly_color
http://www.hpl.hp.com/personal/Giordano_Beretta/
Beretta, Moroney Cognitive Aspects of Color