Download - Towards robust categorical colour perception
Towards robust categorical colour perception
G. Beretta N. Moroney J. Recker
Print Production Automation LabHewlett-Packard Laboratories
Palo Alto, California
11th Congress of the International Colour AssociationSydney, 27 September – 2 October 2009
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 1 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 2 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 3 / 31
Describing colours
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 4 / 31
HTML colour specification
#007CB0#EF4123
#848688
#BF1E74
#F89F6D
#008F4C
#F499B8
#007CB0
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 5 / 31
Automatic layout in variable data printing
automaticlayout
HP chicletnew palette
Buy HPworkstation xw 8600
HP chicletold palette
Buy HPcomputers
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 6 / 31
The wide xvYCC gamut
16
235254
16 240 254
Y
Cb, Cr1
65.0+5.0+5.0-
128
-0.57 Black
Over White
0 < R’,G’,B’ < 1
1< R’,G’,B’
R’,G’,B’< 0
(Gamut of BT.709-5)
Gamut of xvYCC
Extended
Extended Region
Extended Region
R’,G’,B’< 0
1< R’,G’,B’
Extended
BT.709-5(sRGB)
sYCC
xvYCC
0.0
1.0
Luma
Chroma
(sRGB)
1
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 7 / 31
Applications of colour naming
Better user experience in GUIsAutomatic nudging of text and logo colours for readability invariable data printingGamut mapping for HDR and wide gamut displays
Culture-independent preferred color renderingThematic rendering
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 8 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 9 / 31
Local colour differences
Stiles Line ElementEllipses plotted 3 x
y
x
0.8
0.2
0.4
0.6
0 0.2 0.4 0.6
700
450
460470
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610620
630
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 10 / 31
Categorisation
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 11 / 31
Categorical perception
Definition (Stevan Harnad)A categorical perception effect occurs when
1 a set of stimuli ranging along a physical continuum is given onelabel on one side of a category boundary and another label on theother side and
2 the subject can discriminate smaller physical differences betweenpairs of stimuli that straddle boundary than between pairs that areentirely within one category or the other
.55
.45
.35
.25
.15.05 .15 .25 .35 .45
v’
u’
David L. Post, 1988
green
white yelloworange
red
peachaqua
graypink
bluepurple
1. 1. 1.
1..98 .92 .65 .53
.99 .98 .97 .88 .62.97 .91 .94 .84 .66 .5.71 .71 .68 .7 .44
.33
.73 87.91.87 .53.71.59.73.74.57.33.46.44.31
.75.88.96.98.58.54.63.59 .5
.39
.45
.49.63.78.81.63.47.33.35.56.61.61.52
.98.96.93.52
.51
.61.53.53 .47.47
.47.52.41.45
.64
.56 .43.56
.56
.53
.48 .3
.57.56.44
.77.63.38
.82.65.36
.69.42
.39
.45.45
.47.48.28
.37.38
.36
.35
.53.64 .5
.62.75 .53
.74.82.53
.9.84 .48.92.89.53
.98 .9.52
.98 .9 .53
.97 .9
.96.91 .6
.97.92.63
.97.94
.97
.32.46.56.68.76 .74.75.58 .35.53 .7 .8 .85.87.82.74.52.74.81.87.91.89.86
.33.57.69.83.92.88.87.57 .7 .82.86.88.56.68.72.74
.51.63
.5
.48.44
.56.56.47.54.67.77.59.48.7 .83 .8 .72.65.82.92 .9 .75.69.83.93.89.81.83.94.92
.52.91.95
.84B = CIE Standard Illuminant B
E = equal-energy pointD = CIE Standard Illuminant D65C = CIE Standard Illuminant C
A = CIE Standard Illuminant A
A
BED
C.55
.45
.35
.25
.15.05 .15 .25 .35 .45
v’
u’
David L. Post, 1988
green
white yelloworange
red
peachaqua
graypink
bluepurple
1. 1. 1.
1..98 .92 .65 .53
.99 .98 .97 .88 .62.97 .91 .94 .84 .66 .5.71 .71 .68 .7 .44
.33
.73 87.91.87 .53.71.59.73.74.57.33.46.44.31
.75.88.96.98.58.54.63.59 .5
.39
.45
.49.63.78.81.63.47.33.35.56.61.61.52
.98.96.93.52
.51
.61.53.53 .47.47
.47.52.41.45
.64
.56 .43.56
.56
.53
.48 .3
.57.56.44
.77.63.38
.82.65.36
.69.42
.39
.45.45
.47.48.28
.37.38
.36
.35
.53.64 .5
.62.75 .53
.74.82.53
.9.84 .48.92.89.53
.98 .9.52
.98 .9 .53
.97 .9
.96.91 .6
.97.92.63
.97.94
.97
.32.46.56.68.76 .74.75.58 .35.53 .7 .8 .85.87.82.74.52.74.81.87.91.89.86
.33.57.69.83.92.88.87.57 .7 .82.86.88.56.68.72.74
.51.63
.5
.48.44
.56.56.47.54.67.77.59.48.7 .83 .8 .72.65.82.92 .9 .75.69.83.93.89.81.83.94.92
.52.91.95
.84B = CIE Standard Illuminant B
E = equal-energy pointD = CIE Standard Illuminant D65C = CIE Standard Illuminant C
A = CIE Standard Illuminant A
A
BED
C
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 12 / 31
Global colour differences — how to find them?
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
T
V
A = 20
Anatolian brown
cement greybroken warm white
Roman ochre
brown beige
Arsigont
Pompeian yellow
orange ochreIndian orange
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 13 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 14 / 31
Colour ontogeny of languages
Brent Berlin and Paul Kay, University of Berkeley, 1969The physiology underlying even the unique hues is unknownThere is no natural categorisation
yellow
red
greenyellow
green
blue brownwhiteandblack
orangeand/orpinkand/orpurpleand/orgray
I II III IV VI VIIV
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 15 / 31
Development of colour naming
Colour naming is acquired, not geneticsocio-economic status (SES)Franklin et al., PNAS 105(9): 3221–3225, 2008
adultswithin-categorybetween-category
visual fieldleft right
initia
tion t
ime
[ms]
550
250
350
450
infantswithin-categorybetween-category
visual fieldleft right
initia
tion t
ime
[ms]
900
500
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800
Occurs late in child’s development, but age is decreasing withincrease of technology
1900: basic four colours @ 8 years1950: @ 5 years of age
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 16 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 17 / 31
Goal
1 Large dictionarycurrently harvesting unconstrained namesextensive, through crowd-sourcingevolves through timenot limited to one language
2 Number of synonym categories� 12decided though crowd-sourcingnot 266 like in ISCC–NBS thesaurus. . . or 26, or 30, or 80. . .
3 Algorithm for determining categoriesconstruct separate categorisations for each colour patchexplicitly ask user for a specific and a general nameexplore boundary-finding algorithms
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 18 / 31
Multilingual colour naming experiment
http://www.hpl.hp.com/personal/Nathan_Moroney/mlcn.html
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 19 / 31
The colour thesaurus
http://www.hpl.hp.com/personal/Nathan_Moroney/color-thesaurus.html
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 20 / 31
From colour naming to thesaurus
inverse YCiCii
neighbors
CIECAM02 neighbors
core vocabulary
frequency analysis
scrubbed corpus
substring statistics
merging
spell-checker
exclusionary corpus
conventional usage
substitutionsdeletionstypographic
harmonizationraw corpus
naming experiment
synonyms
antonyms
threshold number unique IP addresses
for each name
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 21 / 31
Contributed name distribution
0
400
800
1200
1600
2000
brickemerald
leaf green
eggplantchocolate
cornflower
blue gray
fluorescent green
kelly green
burnt orange
khakibright blue
beigerosepeach
grass green
sea green
periwinkle
lilacmaroonlight blue
turquoiseyellow
magentaredgreen
greenbluepurplepinkredblacklime greenbrownmagentavioletsky blueorangeyellowteallight greenfuchsiaturquoiseaquaroyal blueforest
light bluelavendergraynavy bluemaroonlimedark bluedark greenlilacoliveolive greencyanperiwinklemint greenbright greenmauvesea greenhot pinkneon greenseafoam
grass greentanyellow greennavypeachburgundysalmonlight purplerosegoldplumbrick redbeigemustardwhiteindigobright bluechartreuselight brownaquamarine
khakidark browndark purplemoss greenburnt orangespring greenpea greenbaby bluekelly greendark pinkrustblue greenfluorescent greensagehunter greenpale greenblue graycobaltmidnight bluelight pink
cornflowercreamred orangedark redchocolatecrimsoncoralapple greeneggplantgoldenrodmedium blueocean blueleaf greenbright purplegrapelight yellowemeraldjadeochrearmy greenbrick
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 22 / 31
Handling missing names
corpus scrubbingraw corpusnaming
experiment
synonyms and antonyms
lexical analysis
name found
name harvesting
TRUE
FALSE
crowd
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 23 / 31
Expanding the corpus
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 24 / 31
Robustness: qualifying the corpus
Problems:we observed about3% disruptiveparticipants in theexperimentvariability of rarelyused names
Solution is to collectexplicit feedback on theglobal statistics fromeach participantMore efficient thanrecruiting domainspecialists
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 25 / 31
Feedback distribution
correct, spot on
good
neutral
poor
wrong, completely wrong
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 26 / 31
Outline
1 Problems
2 Global vs. local colour differences
3 What and where are the categories?
4 New paradigm: use crowd-sourcing
5 Status & conclusions
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 27 / 31
What we have so far
Framework for collecting colour names in multiple languagesRobust: colour thesaurus served 194’369 color names as ofWednesday the 23rd of September 2009Robust: feedback mechanism for improving the corpus qualitywith useMechanism to harvest less common namesStill cheating on categorisation: synthetic synonyms vs.categories, but making progress . . .
Experimenting with linguistic analysis tools to find categoryboundaries
No user interface yet to collect category names and antonyms
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 28 / 31
Is the category hierarchy just 2 deep?
Coloroid color
yellow
orange
yellowish orange 1
broken warm white
cement grey
Anatolian brown
Roman ochre
brown beige
Arsigont
Pompeian yellow
orange ochre
Indian ochre
yellowish orange 2
orange 1
orange 2
orange 3
reddish orange 1
reddish orange 2
red
violet
blue
green1
green2
7 domains 48 basics 369 names +79 synonyms
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 29 / 31
Dendrogram — good things to come . . .0
12
34
Heigh
t
shiny
plas
ticglos
ssticky
med
ium.w
eigh
tmed
ium
photo
wax
yultra
flat
coated
viny
lsm
ooth
dull
diffu
seoff.white
semi
semi.glos
stran
spar
ent
clea
rthin
light.w
eigh
tpa
leivory
yello
wcrea
mbe
ige
soft
eggs
hell
chalky
blue
gree
ngr
aysa
tinde
cora
tive
grain
texture
roug
hbr
own
pear
lmetallic
silver
high
parchm
ent
tan
offic
ematte
pape
r white art
rigid
surfac
eco
lor
canv
aslin
enfin
epa
ttern
heav
y.weigh
the
avy
card
thick
stiff
bright
gold
see: Moroney & Beretta,“Nominal scaling of print substrates,” CIC 17,Albuquerque, November 2009
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 30 / 31
Questions and Discussion
http://www.hpl.hp.com/personal/Giordano_Beretta/http://www.hpl.hp.com/personal/Nathan_Moroney/http://www.hpl.hp.com/people/john_recker/blog: http://mostlycolor.ch
Beretta, Moroney, Recker (HP Labs) Towards robust categorical colour perception AIC 2009 31 / 31