Color Name Applications in Computer Vision
Parraga, Carlos Alejandro (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Akbarinia, Arash (Justus-Liebig-Universität Gießen)
Shamey, Renzo ed.

Imprint:	Berlin, Heidelberg : Springer, 2020
Description:	7 pàg.
Abstract:	In Computer Vision, the association of names to colors is one of the fundamental problems in the field of image understanding. There are numerous computational applications (e. g. image retrieval, visual tracking, person identification, human-machine interaction, etc. ) that require pixels to be labelled according to the color perceived by the user. This is relatively easy for focal colors under canonical illuminants, where the agreement is high, but becomes increasingly difficult as perceptions move away from these conditions. For these difficult cases, the traditional solution tends to be a collection of "ad-hoc" strategies, however, new approaches that combine knowledge from anthropology, linguistics, visual perception and machine learning have offered promising results. Specifically, deep neural networks appear to possess all the required building blocks to offer a color naming solution "in the wild". This article reviews the current state of knowledge and discusses open challenges with a multidisciplinary (and non-specialized) readership in mind.
Rights:	Tots els drets reservats.
Language:	Anglès
Document:	Capítol de llibre ; recerca ; Versió acceptada per publicar
Published in:	Encyclopedia of Color Science and Technology, 2020, p. 1-7, ISBN 9783642278518

DOI: 10.1007/978-3-642-27851-8_404-1

Postprint 11 p, 580.8 KB

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