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1.
J Vis ; 18(13): 19, 2018 12 03.
Artigo em Inglês | MEDLINE | ID: mdl-30593061

RESUMO

The human visual system supports stable percepts of object color even though the light that reflects from object surfaces varies significantly with the scene illumination. To understand the computations that support stable color perception, we study how estimating a target object's luminous reflectance factor (LRF; a measure of the light reflected from the object under a standard illuminant) depends on variation in key properties of naturalistic scenes. Specifically, we study how variation in target object reflectance, illumination spectra, and the reflectance of background objects in a scene impact estimation of a target object's LRF. To do this, we applied supervised statistical learning methods to the simulated excitations of human cone photoreceptors, obtained from labeled naturalistic images. The naturalistic images were rendered with computer graphics. The illumination spectra of the light sources and the reflectance spectra of the surfaces in the scene were generated using statistical models of natural spectral variation. Optimally decoding target object LRF from the responses of a small learned set of task-specific linear receptive fields that operate on a contrast representation of the cone excitations yields estimates that are within 13% of the correct LRF. Our work provides a framework for evaluating how different sources of scene variability limit performance on luminance constancy.


Assuntos
Percepção de Cores/fisiologia , Luz , Iluminação , Reconhecimento Visual de Modelos/fisiologia , Células Fotorreceptoras Retinianas Cones/fisiologia , Feminino , Humanos , Masculino , Modelos Estatísticos , Estimulação Luminosa
2.
J Vis ; 14(2)2014 Feb 07.
Artigo em Inglês | MEDLINE | ID: mdl-24511145

RESUMO

RenderToolbox3 provides MATLAB utilities and prescribes a workflow that should be useful to researchers who want to employ graphics in the study of vision and perhaps in other endeavors as well. In particular, RenderToolbox3 facilitates rendering scene families in which various scene attributes and renderer behaviors are manipulated parametrically, enables spectral specification of object reflectance and illuminant spectra, enables the use of physically based material specifications, helps validate renderer output, and converts renderer output to physical units of radiance. This paper describes the design and functionality of the toolbox and discusses several examples that demonstrate its use. We have designed RenderToolbox3 to be portable across computer hardware and operating systems and to be free and open source (except for MATLAB itself). RenderToolbox3 is available at https://github.com/DavidBrainard/RenderToolbox3.


Assuntos
Cognição/fisiologia , Percepção de Cores/fisiologia , Computadores , Sinais (Psicologia) , Reconhecimento Visual de Modelos/fisiologia , Mascaramento Perceptivo/fisiologia , Software , Algoritmos , Humanos , Estimulação Luminosa/métodos
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