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| Author | Xavier Otazu; C. Alejandro Parraga; Maria Vanrell |
 
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| Title | Towards a unified chromatic inducction model | Type | Journal Article | |||
| Year | 2010 | Publication | Journal of Vision | Abbreviated Journal  |
VSS | |
| Volume | 10 | Issue | 12:5 | Pages | 1-24 | |
| Keywords | Visual system; Color induction; Wavelet transform | |||||
| Abstract | In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ OPV2010 | Serial | 1450 | |||
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| Author | C. Alejandro Parraga; Jordi Roca; Maria Vanrell |
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| Title | Do Basic Colors Influence Chromatic Adaptation? | Type | Journal Article | |||
| Year | 2011 | Publication | Journal of Vision | Abbreviated Journal |
VSS | |
| Volume | 11 | Issue | 11 | Pages | 85 | |
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| Abstract | Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered. | |||||
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| ISSN | 1534-7362 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ PRV2011 | Serial | 1759 | |||
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| Author | Javier Vazquez; J. Kevin O'Regan; Maria Vanrell; Graham D. Finlayson |
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| Title | A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation | Type | Journal Article | |||
| Year | 2012 | Publication | Journal of Vision | Abbreviated Journal |
VSS | |
| Volume | 12 | Issue | 6 (7) | Pages | 1-14 | |
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| Abstract | When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VOV2012 | Serial | 1998 | |||
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| Author | Xavier Otazu; Maria Vanrell; C. Alejandro Parraga |
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| Title | Multiresolution Wavelet Framework Models Brightness Induction Effects | Type | Journal | |||
| Year | 2008 | Publication | Vision Research | Abbreviated Journal |
VR | |
| Volume | 48 | Issue | 5 | Pages | 733–751 | |
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ OVP2008a | Serial | 927 | |||
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| Author | Ivet Rafegas; Maria Vanrell |
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| Title | Color encoding in biologically-inspired convolutional neural networks | Type | Journal Article | |||
| Year | 2018 | Publication | Vision Research | Abbreviated Journal |
VR | |
| Volume | 151 | Issue | Pages | 7-17 | ||
| Keywords | Color coding; Computer vision; Deep learning; Convolutional neural networks | |||||
| Abstract | 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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| Notes | CIC; 600.051; 600.087 | Approved | no | |||
| Call Number | Admin @ si @RaV2018 | Serial | 3114 | |||
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| Author | Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell |
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| Title | Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures | Type | Journal Article | |||
| Year | 2011 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal |
TPAMI | |
| Volume | 33 | Issue | 5 | Pages | 917-930 | |
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| Abstract | The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost. | |||||
| Address | Los Alamitos; CA; USA; | |||||
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| Publisher | IEEE Computer Society | Place of Publication | Editor | |||
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| Series Volume | Series Issue | Edition | ||||
| ISSN | 0162-8828 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VBW2011 | Serial | 1715 | |||
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| Author | Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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| Title | Low-level SpatioChromatic Grouping for Saliency Estimation | Type | Journal Article | |||
| Year | 2013 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal |
TPAMI | |
| Volume | 35 | Issue | 11 | Pages | 2810-2816 | |
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| Abstract | We propose a saliency model termed SIM (saliency by induction mechanisms), which is based on a low-level spatiochromatic model that has successfully predicted chromatic induction phenomena. In so doing, we hypothesize that the low-level visual mechanisms that enhance or suppress image detail are also responsible for making some image regions more salient. Moreover, SIM adds geometrical grouplets to enhance complex low-level features such as corners, and suppress relatively simpler features such as edges. Since our model has been fitted on psychophysical chromatic induction data, it is largely nonparametric. SIM outperforms state-of-the-art methods in predicting eye fixations on two datasets and using two metrics. | |||||
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| ISSN | 0162-8828 | ISBN | Medium | |||
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| Notes | CIC; 600.051; 600.052; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ MVO2013 | Serial | 2289 | |||
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| Author | Javier Vazquez; Maria Vanrell; Ramon Baldrich; Francesc Tous |
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| Title | Color Constancy by Category Correlation | Type | Journal Article | |||
| Year | 2012 | Publication | IEEE Transactions on Image Processing | Abbreviated Journal |
TIP | |
| Volume | 21 | Issue | 4 | Pages | 1997-2007 | |
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| Abstract | Finding color representations which are stable to illuminant changes is still an open problem in computer vision. Until now most approaches have been based on physical constraints or statistical assumptions derived from the scene, while very little attention has been paid to the effects that selected illuminants have
on the final color image representation. The novelty of this work is to propose perceptual constraints that are computed on the corrected images. We define the category hypothesis, which weights the set of feasible illuminants according to their ability to map the corrected image onto specific colors. Here we choose these colors as the universal color categories related to basic linguistic terms which have been psychophysically measured. These color categories encode natural color statistics, and their relevance across different cultures is indicated by the fact that they have received a common color name. From this category hypothesis we propose a fast implementation that allows the sampling of a large set of illuminants. Experiments prove that our method rivals current state-of-art performance without the need for training algorithmic parameters. Additionally, the method can be used as a framework to insert top-down information from other sources, thus opening further research directions in solving for color constancy. |
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| ISSN | 1057-7149 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ VVB2012 | Serial | 1999 | |||
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| Author | Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias |
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| Title | Understanding trained CNNs by indexing neuron selectivity | Type | Journal Article | |||
| Year | 2020 | Publication | Pattern Recognition Letters | Abbreviated Journal |
PRL | |
| Volume | 136 | Issue | Pages | 318-325 | ||
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| Abstract | The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understanding of the representations they build and how these representations are organized. To help understanding these issues, we propose to describe the activity of individual neurons by their Neuron Feature visualization and quantify their inherent selectivity with two specific properties. We explore selectivity indexes for: an image feature (color); and an image label (class membership). Our contribution is a framework to seek or classify neurons by indexing on these selectivity properties. It helps to find color selective neurons, such as a red-mushroom neuron in layer Conv4 or class selective neurons such as dog-face neurons in layer Conv5 in VGG-M, and establishes a methodology to derive other selectivity properties. Indexing on neuron selectivity can statistically draw how features and classes are represented through layers in a moment when the size of trained nets is growing and automatic tools to index neurons can be helpful. | |||||
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| Notes | CIC; 600.087; 600.140; 600.118 | Approved | no | |||
| Call Number | Admin @ si @ RVL2019 | Serial | 3310 | |||
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| Author | Susana Alvarez; Maria Vanrell |
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| Title | Texton theory revisited: a bag-of-words approach to combine textons | Type | Journal Article | |||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal |
PR | |
| Volume | 45 | Issue | 12 | Pages | 4312-4325 | |
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| Abstract | The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets. |
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| ISSN | 0031-3203 | ISBN | Medium | |||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ AlV2012a | Serial | 2130 | |||
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| Author | Javier Vazquez; C. Alejandro Parraga; Maria Vanrell |
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| Title | Ordinal pairwise method for natural images comparison | Type | Journal Article | |||
| Year | 2009 | Publication | Perception | Abbreviated Journal |
PER | |
| Volume | 38 | Issue | Pages | 180 | ||
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| Abstract | 38(Suppl.)ECVP Abstract Supplement
We developed a new psychophysical method to compare different colour appearance models when applied to natural scenes. The method was as follows: two images (processed by different algorithms) were displayed on a CRT monitor and observers were asked to select the most natural of them. The original images were gathered by means of a calibrated trichromatic digital camera and presented one on top of the other on a calibrated screen. The selection was made by pressing on a 6-button IR box, which allowed observers to consider not only the most natural but to rate their selection. The rating system allowed observers to register how much more natural was their chosen image (eg, much more, definitely more, slightly more), which gave us valuable extra information on the selection process. The results were analysed considering both the selection as a binary choice (using Thurstone's law of comparative judgement) and using Bradley-Terry method for ordinal comparison. Our results show a significant difference in the rating scales obtained. Although this method has been used in colour constancy algorithm comparisons, its uses are much wider, eg to compare algorithms of image compression, rendering, recolouring, etc. |
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ VPV2009b | Serial | 1191 | |||
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| Author | Robert Benavente; C. Alejandro Parraga; Maria Vanrell |
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| Title | Colour categories boundaries are better defined in contextual conditions | Type | Journal Article | |||
| Year | 2009 | Publication | Perception | Abbreviated Journal |
PER | |
| Volume | 38 | Issue | Pages | 36 | ||
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| Abstract | In a previous experiment [Parraga et al, 2009 Journal of Imaging Science and Technology 53(3)] the boundaries between basic colour categories were measured by asking subjects to categorize colour samples presented in isolation (ie on a dark background) using a YES/NO paradigm. Results showed that some boundaries (eg green – blue) were very diffuse and the subjects' answers presented bimodal distributions, which were attributed to the emergence of non-basic categories in those regions (eg turquoise). To confirm these results we performed a new experiment focussed on the boundaries where bimodal distributions were more evident. In this new experiment rectangular colour samples were presented surrounded by random colour patches to simulate contextual conditions on a calibrated CRT monitor. The names of two neighbouring colours were shown at the bottom of the screen and subjects selected the boundary between these colours by controlling the chromaticity of the central patch, sliding it across these categories' frontier. Results show that in this new experimental paradigm, the formerly uncertain inter-colour category boundaries are better defined and the dispersions (ie the bimodal distributions) that occurred in the previous experiment disappear. These results may provide further support to Berlin and Kay's basic colour terms theory. | |||||
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| Call Number | CAT @ cat @ BPV2009 | Serial | 1192 | |||
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| Author | C. Alejandro Parraga; Javier Vazquez; Maria Vanrell |
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| Title | A new cone activation-based natural images dataset | Type | Journal Article | |||
| Year | 2009 | Publication | Perception | Abbreviated Journal |
PER | |
| Volume | 36 | Issue | Pages | 180 | ||
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| Abstract | We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website. | |||||
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ PVV2009 | Serial | 1193 | |||
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| Author | C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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| Title | Towards a general model of colour categorization which considers context | Type | Journal Article | |||
| Year | 2010 | Publication | Perception. ECVP Abstract Supplement | Abbreviated Journal |
PER | |
| Volume | 39 | Issue | Pages | 86 | ||
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| Abstract | In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours. Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space. |
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ PBV2010b | Serial | 1326 | |||
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