Colour Constancy: Biologically-inspired Contrast Variant Pooling Mechanism

Pooling is a ubiquitous operation in image processing algorithms that allows for higher-level processes to collect relevant low-level features from a region of interest. Currently, max-pooling is one of the most commonly used operators in the computational literature. However, it can lack robustness to outliers due to the fact that it relies merely on the peak of a function. Pooling mechanisms are also present in the primate visual cortex where neurons of higher cortical areas pool signals from lower ones. The receptive fields of these neurons have been shown to vary according to the contrast by aggregating signals over a larger region in the presence of low contrast stimuli. We hypothesise that this contrast-variant-pooling mechanism can address some of the shortcomings of max-pooling. We modelled this contrast variation through a histogram clipping in which the percentage of pooled signal is inversely proportional to the local contrast of an image. We tested our hypothesis by applying it to the phenomenon of colour constancy where a number of popular algorithms utilise a max-pooling step (e.g. White-Patch, Grey-Edge and Double-Opponency). For each of these methods, we investigated the consequences of replacing their original max-pooling by the proposed contrast-variant-pooling. Our experiments on three colour constancy benchmark datasets suggest that previous results can significantly improve by adopting a contrast-variant-pooling mechanism

Feeling Blue or Seeing Red? Similar Patterns of Emotion Associations With Colour Patches and Colour Terms

For many, colours convey affective meaning. Popular opinion assumes that perception of colour is crucial to influence emotions. However, scientific studies test colour–emotion relationships by presenting colours as patches or terms. When using patches, researchers put great effort into colour presentation. When using terms, researchers have much less control over the colour participants think of. In this between-subjects study, we tested whether emotion associations with colour differ between terms and patches. Participants associated 20 emotion concepts, loading on valence, arousal, and power dimensions, with 12 colours presented as patches (n = 54) or terms (n = 78). We report high similarity in the pattern of associations of specific emotion concepts with terms and patches (r = .82), for all colours except purple (r = .−23). We also observed differences for black, which is associated with more negative emotions and of higher intensity when presented as a term than a patch. Terms and patches differed little in terms of valence, arousal, and power dimensions. Thus, results from studies on colour–emotion relationships using colour terms or patches should be largely comparable. It is possible that emotions are associated with colour concepts rather than particular perceptions or words of colour

Colour-emotion associations in individuals with red-green colour blindness

Colours and emotions are associated in languages and traditions. Some of us may convey sadness by saying feeling blue or by wearing black clothes at funerals. The first example is a conceptual experience of colour and the second example is an immediate perceptual experience of colour. To investigate whether one or the other type of experience more strongly drives colour-emotion associations, we tested 64 congenitally red-green colour-blind men and 66 non-colour-blind men. All participants associated 12 colours, presented as terms or patches, with 20 emotion concepts, and rated intensities of the associated emotions. We found that colour-blind and non-colour-blind men associated similar emotions with colours, irrespective of whether colours were conveyed via terms (r = .82) or patches (r = .80). The colour-emotion associations and the emotion intensities were not modulated by participants’ severity of colour blindness. Hinting at some additional, although minor, role of actual colour perception, the consistencies in associations for colour terms and patches were higher in non-colour-blind than colour-blind men. Together, these results suggest that colour-emotion associations in adults do not require immediate perceptual colour experiences, as conceptual experiences are sufficient

NICE : A Computational solution to close the gap from colour perception to colour categorization

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms

Typical chromatic categorization results of NICE shown for two different natural scenes.

<p>Coloured panels show the original image and subsequent panels show the value of “P” for each colour and category.</p

Details of an exemplary 3D-ellipsoid fitting to the psychophysical results irrespective of experimental condition.

<p>Data points correspond to the boundaries of “blue” with all its neighbours (green, purple and achromatic borders were considered). Black ellipses are the intersections between 3D-ellipsoid and the horizontal planes corresponding to the three Y-levels measured: <b><i>Y</i></b>_{<b><i>low</i></b>} = 11.23, <b><i>Y</i></b>_{<b><i>med</i></b>} = 32.37 and <b><i>L</i></b>_{<b><i>high</i></b>} = 72.90. The A vertical ellipse was inserted to highlight the three points that are necessary to fully determine its curvature. White circles represent the weight exerted in the fit by data points related to each of the nine boundaries measured. All observers and conditions were considered.</p

lsY plot of all experimental results (Conditions 1 and 2).

<p>The scale of the s-axis was chosen so that the StDev of the achromatic boundaries data is the same in both l and s directions (see last row in the 3x3 matrix in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0149538#pone.0149538.e001" target="_blank">Eq 1</a>).</p

Side and top views of our 3D-ellipsoidal fittings to all categorical boundary data in <i>lsY</i> space.

<p>For each category, we considered all points bordering with its categorical neighbours, including the achromatic centre. The ellipsoids’ sizes and positions were calculated by minimizing the planar distances between the points and the ellipses generated by intersecting the 3D-ellipsoid with the six constant-Y (horizontal) planes described in the main text. The top view also includes the triangle formed by the monitor’s RGB phosphorous.</p

Schematics of the experiment.

<p>Subjects manipulated the hue of a central test patch using a gamepad (left). The test patch was embedded inside a coloured Mondrian (Condition 1) or a mid-lightness grey background (Condition 2). Two colour names were presented at the bottom of the screen and subjects had to produce colours equally distant from those represented by the names. They were only allowed to modify the colour along predetermined paths (e.g. lines or concentric arches of randomised radius in CIE L*a*b* space), which started and ended well inside the consensus colour-name regions corresponding to the colour names on the screen. There were no time or head movement constraints.</p