Literature DB >> 29951192

The perception of colour and material in naturalistic tasks.

David H Brainard1, Nicolas P Cottaris1, Ana Radonjić1.   

Abstract

Perceived object colour and material help us to select and interact with objects. Because there is no simple mapping between the pattern of an object's image on the retina and its physical reflectance, our perceptions of colour and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work, particularly as they act to stabilize perceived colour and material against variation in scene factors extrinsic to object surface properties, such as the illumination. If we take seriously the notion that perceived colour and material are useful because they help guide behaviour in natural tasks, then we need experiments that measure and models that describe how they are used in such tasks. To this end, we have developed selection-based methods and accompanying perceptual models for studying perceived object colour and material. This focused review highlights key aspects of our work. It includes a discussion of future directions and challenges, as well as an outline of a computational observer model that incorporates early, known, stages of visual processing and that clarifies how early vision shapes selection performance.

Keywords:  colour constancy; colour perception; computational models; material perception; psychophysics

Year:  2018        PMID: 29951192      PMCID: PMC6015813          DOI: 10.1098/rsfs.2018.0012

Source DB:  PubMed          Journal:  Interface Focus        ISSN: 2042-8898            Impact factor:   3.906


  62 in total

1.  Maximum likelihood difference scaling.

Authors:  Laurence T Maloney; Joong Nam Yang
Journal:  J Vis       Date:  2003-10-07       Impact factor: 2.240

2.  Lightness identification of patterned three-dimensional, real objects.

Authors:  Rocco Robilotto; Qasim Zaidi
Journal:  J Vis       Date:  2006-01-13       Impact factor: 2.240

3.  The retinex theory of color vision.

Authors:  E H Land
Journal:  Sci Am       Date:  1977-12       Impact factor: 2.142

4.  Colour Vision: Understanding #TheDress.

Authors:  David H Brainard; Anya C Hurlbert
Journal:  Curr Biol       Date:  2015-06-29       Impact factor: 10.834

5.  Coupled computations of three-dimensional shape and material.

Authors:  Phillip J Marlow; Dejan Todorović; Barton L Anderson
Journal:  Curr Biol       Date:  2015-03-16       Impact factor: 10.834

6.  Influence of optical material properties on the perception of liquids.

Authors:  Jan Jaap R van Assen; Roland W Fleming
Journal:  J Vis       Date:  2016-12-01       Impact factor: 2.240

7.  Comparing sensitivity estimates from MLDS and forced-choice methods in a slant-from-texture experiment.

Authors:  Guillermo Aguilar; Felix A Wichmann; Marianne Maertens
Journal:  J Vis       Date:  2017-01-01       Impact factor: 2.240

8.  Bias effects of short- and long-term color memory for unique objects.

Authors:  Marina Bloj; David Weiß; Karl R Gegenfurtner
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2016-04-01       Impact factor: 2.129

9.  Factors underlying individual differences in the color matches of normal observers.

Authors:  M A Webster; D I MacLeod
Journal:  J Opt Soc Am A       Date:  1988-10       Impact factor: 2.129

10.  Simultaneous colour constancy revisited: an analysis of viewing strategies.

Authors:  F W Cornelissen; E Brenner
Journal:  Vision Res       Date:  1995-09       Impact factor: 1.886

View more
  2 in total

1.  The relative contribution of color and material in object selection.

Authors:  Ana Radonjić; Nicolas P Cottaris; David H Brainard
Journal:  PLoS Comput Biol       Date:  2019-04-12       Impact factor: 4.475

2.  Modeling visual performance differences 'around' the visual field: A computational observer approach.

Authors:  Eline R Kupers; Marisa Carrasco; Jonathan Winawer
Journal:  PLoS Comput Biol       Date:  2019-05-24       Impact factor: 4.475

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.