Illumination discrimination for chromatically biased illuminations: Implications for color constancy.

We measured discrimination thresholds for illumination changes along different chromatic directions starting from chromatically biased reference illuminations. Participants viewed a Mondrian-papered scene illuminated by LED lamps. The scene was first illuminated by a reference illumination, followed by two comparisons. One comparison matched the reference (the target); the other (the test) varied from the reference, nominally either bluer, yellower, redder, or greener. The participant's task was to correctly select the target. A staircase procedure found thresholds for discrimination of an illumination change along each axis of chromatic change. Nine participants completed the task for five different reference illumination conditions (neutral, blue, yellow, red, and green). We find that relative discrimination thresholds for different chromatic directions of illumination change vary with the reference illumination. For the neutral reference, there is a trend for thresholds to be highest in the bluer illumination-change direction, replicating our previous reports of a "blue bias" for neutral reference illuminations. For the four chromatic references (blue, yellow, red, and green), the change in illumination toward the neutral reference is less well discriminated than changes in the other directions: a "neutral bias." The results have implications for color constancy: In considering the stability of surface appearance under changes in illumination, both the starting chromaticity of the illumination and direction of change must be considered, as well as the chromatic characteristics of the surface reflectance ensemble. They also suggest it will be worthwhile to explore whether and how the human visual system has internalized the statistics of natural illumination changes.

Illumination discrimination in the absence of a fixed surface-reflectance layout.

Previous studies have shown that humans can discriminate spectral changes in illumination and that this sensitivity depends both on the chromatic direction of the illumination change and on the ensemble of surfaces in the scene. These studies, however, always used stimulus scenes with a fixed surface-reflectance layout. Here we compared illumination discrimination for scenes in which the surface reflectance layout remains fixed (fixed-surfaces condition) to those in which surface reflectances were shuffled randomly across scenes, but with the mean scene reflectance held approximately constant (shuffled-surfaces condition). Illumination discrimination thresholds in the fixed-surfaces condition were commensurate with previous reports. Thresholds in the shuffled-surfaces condition, however, were considerably elevated. Nonetheless, performance in the shuffled-surfaces condition exceeded that attainable through random guessing. Analysis of eye fixations revealed that in the fixed-surfaces condition, low illumination discrimination thresholds (across observers) were predicted by low overall fixation spread and high consistency of fixation location and fixated surface reflectances across trial intervals. Performance in the shuffled-surfaces condition was not systematically related to any of the eye-fixation characteristics we examined for that condition, but was correlated with performance in the fixed-surfaces condition.

Illumination discrimination in real and simulated scenes.

Characterizing humans' ability to discriminate changes in illumination provides information about the visual system's representation of the distal stimulus. We have previously shown that humans are able to discriminate illumination changes and that sensitivity to such changes depends on their chromatic direction. Probing illumination discrimination further would be facilitated by the use of computer-graphics simulations, which would, in practice, enable a wider range of stimulus manipulations. There is no a priori guarantee, however, that results obtained with simulated scenes generalize to real illuminated scenes. To investigate this question, we measured illumination discrimination in real and simulated scenes that were well-matched in mean chromaticity and scene geometry. Illumination discrimination thresholds were essentially identical for the two stimulus types. As in our previous work, these thresholds varied with illumination change direction. We exploited the flexibility offered by the use of graphics simulations to investigate whether the differences across direction are preserved when the surfaces in the scene are varied. We show that varying the scene's surface ensemble in a manner that also changes mean scene chromaticity modulates the relative sensitivity to illumination changes along different chromatic directions. Thus, any characterization of sensitivity to changes in illumination must be defined relative to the set of surfaces in the scene.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

Predicting attitudes towards screening for neurodegenerative diseases using OCT and artificial intelligence: Findings from a literature review.

Recent developments in artificial intelligence (AI) and machine learning raise the possibility of screening and early diagnosis for neurodegenerative diseases, using 3D scans of the retina. The eventual value of such screening will depend not only on scientific metrics such as specificity and sensitivity but, critically, also on public attitudes and uptake. Differential screening rates for various screening programmes in England indicate that multiple factors influence uptake. In this narrative literature review, some of these potential factors are explored in relation to predicting uptake of an early screening tool for neurodegenerative diseases using AI. These include: awareness of the disease, perceived risk, social influence, the use of AI, previous screening experience, socioeconomic status, health literacy, uncontrollable mortality risk, and demographic factors. The review finds the strongest and most consistent predictors to be ethnicity, social influence, the use of AI, and previous screening experience. Furthermore, it is likely that factors also interact to predict the uptake of such a tool. However, further experimental work is needed both to validate these predictions and explore interactions between the significant predictors.

Modeling color preference using color space metrics.

Studying color preferences provides a means to discover how perceptual experiences map onto cognitive and affective judgments. A challenge is finding a parsimonious way to describe and predict patterns of color preferences, which are complex with rich individual differences. One approach has been to model color preferences using factors from metric color spaces to establish direct correspondences between dimensions of color and preference. Prior work established that substantial, but not all, variance in color preferences could be captured by weights on color space dimensions using multiple linear regression. The question we address here is whether model fits may be improved by using different color metric specifications. We therefore conducted a large-scale analysis of color space models, and focused in-depth analysis on models that differed in color space (cone-contrast vs. CIELAB), coordinate system within the color space (Cartesian vs. cylindrical), and factor degrees (1st degree only, or 1st and 2nd degree). We used k-fold cross validation to avoid over-fitting the data and to ensure fair comparisons across models. The best model was the 2nd-harmonic Lch model ("LabC Cyl2"). Specified in CIELAB space, it included 1st and 2nd harmonics of hue (capturing opponency in hue preferences and simultaneous liking/disliking of both hues on an opponent axis, respectively), lightness, and chroma. These modeling approaches can be used to characterize and compare patterns for group averages and individuals in future datasets on color preference, or other measures in which correspondences between color appearance and cognitive or affective judgments may exist.

Colour Vision: Understanding #TheDress.

A widely-viewed image of a dress elicits striking individual variation in colour perception. Experiments with multiple variants of the image suggest that the individual differences may arise through the action of visual mechanisms that normally stabilise object colour.

Performance on the Farnsworth-Munsell 100-Hue Test Is Significantly Related to Nonverbal IQ.

PURPOSE: The Farnsworth-Munsell 100-Hue test (FM100) is a standardized measure of chromatic discrimination, based on colored cap-sorting, which has been widely used in both adults and children. Its dependence on seriation ability raises questions as to its universal suitability and accuracy in assessing purely sensory discrimination. This study investigates how general intellectual ability relates to performance on both the FM100 and a new computer-based chromatic discrimination threshold test, across different age groups in both typical and atypical development. METHODS: Participants were divided into two main age groups, children (6-15 years) and young adults (16-25 years), with each group further subdivided into typically developing (TD; three groups; TD 6-7 years, TD 8-9 years, TD Adult) individuals and atypically developing individuals, all but one carrying a diagnosis of Autism Spectrum Disorders (ASD; two groups; atypically developing [ATY] child 7-15 years, ASD Adult). General intelligence was measured using the Wechsler Abbreviated Intelligence Scale and Wechsler Intelligence Scale for Children. All participants completed the FM100. Both child groups also completed a computer-based chromatic discrimination threshold test, which assessed discrimination along cone-opponent ("red-green," "blue-yellow") and luminance cardinal axes using a controlled staircase procedure. RESULTS: Farnsworth-Munsell 100-Hue test performance was better in adults than in children. Furthermore, performance significantly positively correlated with nonverbal intelligence quotient (NVIQ) for all child groups and the young adult ASD group. The slope of this relationship was steeper for the ASD than TD groups. Performance on the chromatic discrimination threshold test was not significantly related to any IQ measure. Regression models reveal that chromatic discrimination threshold, although a significant predictor of FM100 performance when used alone, is a weaker predictor than NVIQ used alone or in combination. CONCLUSIONS: The results indicate that FM100 performance is not purely a measure of color discrimination but instead also reflects general nonverbal ability. Other measures of chromatic discrimination ability are therefore required for its accurate assessment, particularly in early or atypical development.

An empirical study of the traditional Mach card effect.

The traditional achromatic Mach card effect is an example of lightness inconstancy and a demonstration of how shape and lightness perception interact. We present a quantitative study of this phenomenon and explore the conditions under which it occurs. The results demonstrate that observers show lightness constancy only when sufficient information is available about the light-source position, and the perceptual task required of them is surface identification rather than direct colour-appearance matching. An analysis and comparison of these results with the chromatic Mach card effect (Bloj et al 1999 Nature 402 877-879) demonstrate that the luminance effects of mutual illumination do not account for the change in lightness perception in the traditional Mach card.