A computational model of colour categorization

Yendrikhovskij, SN Sergej

doi:10.1002/1520-6378(2001)26:1+<::aid-col50>3.0.co;2-o

Cited by 41 publications

(24 citation statements)

References 10 publications

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“…A natural possibility is that communicative need may be shaped largely by the statistics of colors in the world (e.g. Yendrikhovskij, 2001;Gibson et al, 2017). If this is the case, then a prior derived from the distribution of colors in the environment should provide a good account of color naming.…”

Section: Visual Environmentmentioning

confidence: 99%

Communicative need in colour naming

Zaslavsky

Kemp

Tishby

et al. 2019

Cognitive Neuropsychology

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Color naming across languages has traditionally been held to reflect the structure of color perception. At the same time, it has often, and increasingly, been suggested that color naming may be shaped by patterns of communicative need. However, much remains unknown about the factors involved in communicative need, how need interacts with perception, and how this interaction may shape color naming. Here, we engage these open questions by building on general information-theoretic principles. We present a systematic evaluation of several factors that may reflect need, and that have been proposed in the literature: capacity constraints, linguistic usage, and the visual environment. Our analysis suggests that communicative need in color naming is reflected more directly by capacity constraints and linguistic usage than it is by the statistics of the visual environment.

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Section: Visual Environmentmentioning

confidence: 99%

Communicative need in colour naming

Zaslavsky

Kemp

Tishby

et al. 2019

Cognitive Neuropsychology

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“…It is claimed that these distributions limit the number of possible configurations of the colour category systems. Yendrikhovskij (2001) presented computational simulations that support this view. He demonstrated how the distribution of colours in natural images can be used to extract colour categories that resemble human colour categories.…”

Section: Impact Of Environment On Similarity To Natural Systemsmentioning

confidence: 83%

“…Ever since Berlin & Kay (1969) observed that colour categories show a remarkable cross-cultural similarity, there has been an ongoing debate on what the main cause of this universal character of colour categories might be. Some authors (Van Wijk 1959;Shepard 1992;Yendrikhovskij 2001) claim that this cross-cultural similarity is due to the shared environment in which individuals use their colour categories. These environments exhibit statistical distributions by which colours occur, which are not uniform.…”

Section: Impact Of Environment On Similarity To Natural Systemsmentioning

confidence: 99%

Language strategies for the domain of colour

Bleys¹

2015

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Joris Bleys. 2015. Language strategies for the domain of colour (Computational Models of Language Evolution 3). Berlin: Language Science Press. This title can be downloaded at: http://langsci-press.org/catalog/book/51 © 2015, Joris Bleys Published under the Creative Commons Attribution 4.0 Licence (CC BY 4.0): http://creativecommons.org/licenses/by/4.0/ ISBN: 978-3-946234-16-6 (Digital) 978-3-946234-17-3 (Hardcover) 978-3-944675-44-2 (Softcover) ISSN: 2364-7809Cover and concept of design: Storage and cataloguing done by FU BerlinLanguage Science Press has no responsibility for the persistence or accuracy of URLs for external or third-party Internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate. Information regarding prices, travel timetables and other factual information given in this work are correct at the time of first publication but Language Science Press does not guarantee the accuracy of such information thereafter.

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“…Figure 12 shows the iterative process that generates clusters and centroids. We can note that the K-means clustering analysis was performed in the field of computational modeling of color categorization 28 and data mining for systematic classification of urban form characteristics. 29 A cluster can be assimilated to the collection of individuals based on their affiliations to a type.…”

Section: Development Of a Parametric Color Typologymentioning

confidence: 99%

Color in the urban environment: A user‐oriented protocol for chromatic characterization and the development of a parametric typology

Nguyen

Teller

2016

Color Research & Application

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This article presents a user-oriented protocol that can be used to characterize chromatic attributes of an urban area. A need for both affordable and reliable assessment method of color has been observed in the field of urban design. The challenge is to provide statistical answers to these two questions: how is color organized, how does it develop its own structure in the city? The main purpose of the research is hence to investigate mean color types within the city via the implementation of a characterization tool; an urban area of the four main classes (historic center, periurban housing districts, working-class neighborhoods, and commercial zones) being characterized by a specific color palette, or a layout of specific color types. The developed instrumentation allows the assessment of the homogeneous and consistent features of an urban district. Their characterization protocol was tested through an application to several streets of the city of Lie`ge (Belgium).

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A computational model of colour categorization

Cited by 41 publications

References 10 publications

Communicative need in colour naming

Communicative need in colour naming

Language strategies for the domain of colour

Color in the urban environment: A user‐oriented protocol for chromatic characterization and the development of a parametric typology

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