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Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
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Title |
Names and Shades of Color for Intrinsic Image Estimation |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
278-285 |
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In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. |
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Providence, Rhode Island |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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CIC |
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no |
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Admin @ si @ SPB2012 |
Serial |
2026 |
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Author |
Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras |
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Title |
The Photometry of Intrinsic Images |
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Conference Article |
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Year |
2014 |
Publication |
27th IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
1494-1501 |
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Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. |
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Columbus; Ohio; USA; June 2014 |
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CVPR |
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CIC; 600.052; 600.051; 600.074 |
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no |
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Admin @ si @ SPB2014 |
Serial |
2506 |
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Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell |
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Title |
Contribution of CIWaM in JPEG2000 Quantization for Color Images |
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Conference Article |
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Year |
2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
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Pages |
132–136 |
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The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM(ChromaticInductionWaveletModel). |
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Gjovik (Norway) |
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CREATE |
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CIC |
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no |
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Call Number |
CAT @ cat @ MOV2010b |
Serial |
1308 |
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Author |
Javier Vazquez; Maria Vanrell; Robert Benavente |
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Title |
Color names as a constraint for Computer Vision problems |
Type |
Conference Article |
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Year |
2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
Abbreviated Journal |
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324–328 |
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Computer Vision Problems are usually ill-posed. Constraining de gamut of possible solutions is then a necessary step. Many constrains for different problems have been developed during years. In this paper, we present a different way of constraining some of these problems: the use of color names. In particular, we will focus on segmentation, representation ans constancy. |
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Gjovik (Norway) |
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CREATE |
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CIC |
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no |
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Call Number |
CAT @ cat @ VVB2010 |
Serial |
1328 |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title |
Who Painted this Painting? |
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Conference Article |
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Year |
2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
Abbreviated Journal |
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Pages |
329–333 |
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Address |
Gjovik (Norway) |
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CREATE |
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CIC |
Approved |
no |
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Call Number |
CAT @ cat @ KWV2010 |
Serial |
1329 |
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Permanent link to this record |
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Author |
Robert Benavente; Maria Vanrell |
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Title |
Parametrizacion del Espacio de Categorias de Color |
Type |
Miscellaneous |
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Year |
2007 |
Publication |
Proceedings del VIII Congreso Nacional del Color |
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Pages |
77–78 |
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Address |
Madrid (Spain) |
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Conference |
CNC’07 |
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Notes |
CAT;CIC |
Approved |
no |
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Call Number |
CAT @ cat @ BeV2007 |
Serial |
905 |
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Author |
Robert Benavente; C. Alejandro Parraga; Maria Vanrell |
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Title |
La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas |
Type |
Conference Article |
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Year |
2010 |
Publication |
9th Congreso Nacional del Color |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
92–95 |
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Keywords |
Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos |
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Abstract |
En este artículo presentamos los resultados de un experimento de categorización de color en el que las muestras se presentaron sobre un fondo multicolor (Mondrian) para simular los efectos del contexto. Los resultados se comparan con los de un experimento previo que, utilizando un paradigma diferente, determinó las fronteras sin tener en cuenta el contexto. El análisis de los resultados muestra que las fronteras obtenidas con el experimento en contexto presentan menos confusión que las obtenidas en el experimento sin contexto. |
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Address |
Alicante (Spain) |
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ISBN |
978-84-9717-144-1 |
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CNC |
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Notes |
CIC |
Approved |
no |
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Call Number |
CAT @ cat @ BPV2010 |
Serial |
1327 |
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Permanent link to this record |
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Author |
Ivet Rafegas; Maria Vanrell |
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Title |
Color spaces emerging from deep convolutional networks |
Type |
Conference Article |
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Year |
2016 |
Publication |
24th Color and Imaging Conference |
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Volume |
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Issue |
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Pages |
225-230 |
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Abstract |
Award for the best interactive session
Defining color spaces that provide a good encoding of spatio-chromatic properties of color surfaces is an open problem in color science [8, 22]. Related to this, in computer vision the fusion of color with local image features has been studied and evaluated [16]. In human vision research, the cells which are selective to specific color hues along the visual pathway are also a focus of attention [7, 14]. In line with these research aims, in this paper we study how color is encoded in a deep Convolutional Neural Network (CNN) that has been trained on more than one million natural images for object recognition. These convolutional nets achieve impressive performance in computer vision, and rival the representations in human brain. In this paper we explore how color is represented in a CNN architecture that can give some intuition about efficient spatio-chromatic representations. In convolutional layers the activation of a neuron is related to a spatial filter, that combines spatio-chromatic representations. We use an inverted version of it to explore the properties. Using a series of unsupervised methods we classify different type of neurons depending on the color axes they define and we propose an index of color-selectivity of a neuron. We estimate the main color axes that emerge from this trained net and we prove that colorselectivity of neurons decreases from early to deeper layers. |
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Address |
San Diego; USA; November 2016 |
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CIC |
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no |
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Call Number |
Admin @ si @ RaV2016a |
Serial |
2894 |
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Author |
Hassan Ahmed Sial; S. Sancho; Ramon Baldrich; Robert Benavente; Maria Vanrell |
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Title |
Color-based data augmentation for Reflectance Estimation |
Type |
Conference Article |
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Year |
2018 |
Publication |
26th Color Imaging Conference |
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Pages |
284-289 |
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Abstract |
Deep convolutional architectures have shown to be successful frameworks to solve generic computer vision problems. The estimation of intrinsic reflectance from single image is not a solved problem yet. Encoder-Decoder architectures are a perfect approach for pixel-wise reflectance estimation, although it usually suffers from the lack of large datasets. Lack of data can be partially solved with data augmentation, however usual techniques focus on geometric changes which does not help for reflectance estimation. In this paper we propose a color-based data augmentation technique that extends the training data by increasing the variability of chromaticity. Rotation on the red-green blue-yellow plane of an opponent space enable to increase the training set in a coherent and sound way that improves network generalization capability for reflectance estimation. We perform some experiments on the Sintel dataset showing that our color-based augmentation increase performance and overcomes one of the state-of-the-art methods. |
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Address |
Vancouver; November 2018 |
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CIC |
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no |
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Call Number |
Admin @ si @ SSB2018a |
Serial |
3129 |
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Permanent link to this record |
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Author |
Javier Vazquez; Maria Vanrell; Ramon Baldrich |
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Title |
Towards a Psychophysical Evaluation of Colour Constancy Algorithms |
Type |
Conference Article |
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Year |
2008 |
Publication |
4th European Conference on Colour in Graphics, Imaging and Vision Proceedings |
Abbreviated Journal |
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372–377 |
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Address |
Terrassa (Spain) |
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CGIV08 |
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CAT;CIC |
Approved |
no |
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Call Number |
CAT @ cat @ VVB2008a |
Serial |
968 |
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Permanent link to this record |
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Author |
C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Title |
Modelling Inter-Colour Regions of Colour Naming Space |
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Conference Article |
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Year |
2008 |
Publication |
4th European Conference on Colour in Graphics, Imaging and Vision Proceedings |
Abbreviated Journal |
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218–222 |
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Terrassa (Spain) |
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CGIV08 |
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CAT;CIC |
Approved |
no |
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Call Number |
CAT @ cat @ PBV2008 |
Serial |
969 |
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Permanent link to this record |
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Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell |
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Title |
Local Perceptual Weighting in JPEG2000 for Color Images |
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Conference Article |
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Year |
2010 |
Publication |
5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
Abbreviated Journal |
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255–260 |
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The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model). |
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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CIC |
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no |
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Call Number |
CAT @ cat @ MOV2010a |
Serial |
1307 |
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Permanent link to this record |
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Author |
C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell |
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Title |
Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset |
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Conference Article |
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2010 |
Publication |
5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
Abbreviated Journal |
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50–57 |
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The characterization of trichromatic cameras is usually done in terms of a device-independent color space, such as the CIE 1931 XYZ space. This is indeed convenient since it allows the testing of results against colorimetric measures. We have characterized our camera to represent human cone activation by mapping the camera sensor's (RGB) responses to human (LMS) through a polynomial transformation, which can be “customized” according to the types of scenes we want to represent. Here we present a method to test the accuracy of the camera measures and a study on how the choice of training reflectances for the polynomial may alter the results. |
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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CIC |
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no |
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Call Number |
CAT @ cat @ PBV2010a |
Serial |
1322 |
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Permanent link to this record |
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Author |
Javier Vazquez; G. D. Finlayson; Maria Vanrell |
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Title |
A compact singularity function to predict WCS data and unique hues |
Type |
Conference Article |
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Year |
2010 |
Publication |
5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
Abbreviated Journal |
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33–38 |
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Abstract |
Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors.
Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation.
In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure. |
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Joensuu, Finland |
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Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
9781617388897 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CGIV/MCS |
|
|
Notes |
CIC |
Approved |
no |
|
|
Call Number |
CAT @ cat @ VFV2010 |
Serial |
1324 |
|
Permanent link to this record |