hands on demonstration
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Hands on demonstration. Nature of colour categories. What do we know?. There is evidence that colour categories are universal. All cultures have colour categories that are similar to RED, GREEN, BLUE, YELLOW, and so on. Three possible explanations Genetically determined. - PowerPoint PPT PresentationTRANSCRIPT
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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Hands on demonstrationHands on demonstration
Nature of colour categories
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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What do we know?What do we know?• There is evidence that colour categories are
universal.– All cultures have colour categories that are
similar to RED, GREEN, BLUE, YELLOW, and so on.
• Three possible explanations– Genetically determined.– Culturally (and linguistically) determined.– Ecologically determined.
• In this demonstration we will take a closer look at the last explanation.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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Why do we want to know?Why do we want to know?• Language is about communicating
concepts, we want to now how concepts are acquired.
• As a case study we take colour categories.
• “…this may at first appear to be a comparatively trivial example of some minor aspect of language, but the implications for other aspects of language evolution are truly staggering.” (Deacon, 1997)
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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Hypothesis and assumptionsHypothesis and assumptions• Research question
– Does our ecology contain enough structure to specify colour categories the way they are?
• Hypothesis– Human ecologies contain enough structure to specify
human colour categories.
• Assumptions– No semantics, culture or language is involved.– Colour categories have a prototypical nature.– Colour categories are extracted from chromatic stimuli
in an unsupervised manner.– We choose a representation for our colours that is
psychophysically plausible.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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What do we expect?What do we expect?• If the claim is true:
– Categories extracted from the real-world data should resemble human colour categories.
– Categories extracted from the random data should not resemble human colour categories.
– Categories extracted from real-world data should not resemble the ones from random data.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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ToolsTools• A digital camera.• Matlab (a mathematical package).• SPSS (a statistics package).
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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MethodologyMethodology• Gather image collection from natural and urban
environments.
• Draw 25,000 random pixels from each collection. Construct random set as control.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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MethodologyMethodology• Extract categories from the data
– This we do by unsupervised clustering (k-means clustering) as this does not violate our assumptions.
• Compare the categories to human colour categories– Sturges & Whitfield (1995) have recorded the 11
basic colour categories of American English-speaking informants.
– Quantitative and objective comparing happens through matching couples and calculating the correlation between clusters and human colour categories. We use Kendall’s Tau correlation for ranked and matched observations.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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The colour stimuliThe colour stimuli
natural urban
random
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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Extracted categories versus human categoriesExtracted categories versus human categories
0 10 20 30 40 50 60 70 80 90 1000102030405060708090100
l for Sturges and Whitfield
l for cluster
s
NATURE vs Sturges and Whitfield (1995) in CIElab
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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DemonstrationDemonstration• A quick demonstration of a “light” version
of an experiment.
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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ResultsResults
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l for Sturges and Whitfieldl for c
lusters
NATURE vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80-60-40-20020406080
a for Sturges and Whitfield
a for cluster
s
NATURE vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80 100-60-40-20020406080100
b for Sturges and Whitfield
b for cluster
s
NATURE vs Sturges and Whitfield (1995) in CIElab
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
l for Sturges and Whitfield
l for
clu
sters
URBAN vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80-60-40-20020406080
a for Sturges and Whitfielda for c
lusters
URBAN vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80 100-60-40-20020406080100
b for Sturges and Whitfield
b for cluster
s
URBAN vs Sturges and Whitfield (1995) in CIElab
0 10 20 30 40 50 60 70 80 90 1000102030405060708090100
l for Sturges and Whitfield
l for cluster
s
RANDOM vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80-80-60-40-20020406080
a for Sturges and Whitfield
a for cluster
s
RANDOM vs Sturges and Whitfield (1995) in CIElab
-60 -40 -20 0 20 40 60 80 100-80-60-40-20020406080100
b for Sturges and Whitfieldb for c
lusters
RANDOM vs Sturges and Whitfield (1995) in CIElab
l a b
nature
urban
random
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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CorrelationCorrelationCorrelations between lightness, colour axes, chroma and hue.
Correlation between random
distribution and human
categories is not lower than for a real-world
distribution
For two different colour appearance models (CIE L*a*b* and CIE L*u*v*).
Modelling the evolution of language for modellers and non-modellersIJCAI 2005
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ConclusionConclusion• We could not refute the null hypothesis.
– Clustering random colours produces categories that correlate equally well.
• Human ecologies have only a marginal influence on colour categories.
• What then does have an influence?– Psychophysical properties of colour perception.– The nature of categories (maximally distinct).– And possible culture and language (but no proof
in this experiment).
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More on thisMore on this• Yendrikhovskij, S.N. (2001) Computing Color Categories
from Statistics of Natural Images. Journal of Imaging Science and Technology, 45(5):409-417.
• Belpaeme, T. & Bleys, J. (2004) Does structure in the environment influence our conceptualization? Proceedings of the Conference on the Evolution of Language 2004, Leipzig, Germany.
• Steels, L. & Belpaeme, T. (2005) Coordinating perceptually grounded categories through language: A case study for colour. Behavioral and Brain Sciences, 28(4). In press.