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Robert Benavente; Maria Vanrell; Ramon Baldrich |
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A data set for fuzzy colour naming |
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2006 |
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Color Research & Application, 31(1):48–56 |
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CAT @ cat @ BVB2006 |
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590 |
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M. Gonzalez-Audicana; Xavier Otazu; O. Fors; A. Seco |
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Comparison between Mallats and the trous discrete wavelet transform based algorithms for the fusion of multispectral and panchromatic images |
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2005 |
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International Journal of Remote Sensing, 26(3):595–614 (IF: 0.925) |
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CAT @ cat @ GOF2005 |
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530 |
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Ivet Rafegas; Maria Vanrell |
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Color encoding in biologically-inspired convolutional neural networks |
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2018 |
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Vision Research |
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VR |
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151 |
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7-17 |
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Color coding; Computer vision; Deep learning; Convolutional neural networks |
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Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. |
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CIC; 600.051; 600.087 |
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Admin @ si @RaV2018 |
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3114 |
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Domicele Jonauskaite; Lucia Camenzind; C. Alejandro Parraga; Cecile N Diouf; Mathieu Mercapide Ducommun; Lauriane Müller; Melanie Norberg; Christine Mohr |
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Colour-emotion associations in individuals with red-green colour blindness |
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2021 |
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PeerJ |
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9 |
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e11180 |
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Affect; Chromotherapy; Colour cognition; Colour vision deficiency; Cross-modal correspondences; Daltonism; Deuteranopia; Dichromatic; Emotion; Protanopia. |
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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. |
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CIC; LAMP; 600.120; 600.128 |
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Admin @ si @ JCP2021 |
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3564 |
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Trevor Canham; Javier Vazquez; Elise Mathieu; Marcelo Bertalmío |
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Matching visual induction effects on screens of different size |
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2021 |
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Journal of Vision |
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JOV |
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21 |
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6(10) |
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1-22 |
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In the film industry, the same movie is expected to be watched on displays of vastly different sizes, from cinema screens to mobile phones. But visual induction, the perceptual phenomenon by which the appearance of a scene region is affected by its surroundings, will be different for the same image shown on two displays of different dimensions. This phenomenon presents a practical challenge for the preservation of the artistic intentions of filmmakers, because it can lead to shifts in image appearance between viewing destinations. In this work, we show that a neural field model based on the efficient representation principle is able to predict induction effects and how, by regularizing its associated energy functional, the model is still able to represent induction but is now invertible. From this finding, we propose a method to preprocess an image in a screen–size dependent way so that its perception, in terms of visual induction, may remain constant across displays of different size. The potential of the method is demonstrated through psychophysical experiments on synthetic images and qualitative examples on natural images. |
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Admin @ si @ CVM2021 |
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3595 |
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