| Records |
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| Author |
Robert Benavente; Ramon Baldrich; M.C. Olive; Maria Vanrell |
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Title  |
Colour Naming Considering the Colour Variability Problem. |
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Miscellaneous |
| Year |
2000 |
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Computacion y Sistemas, 4(1):30–43. |
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no |
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CAT @ cat @ BBO2000 |
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242 |
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| Author |
Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |
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| Title |
Colour Normalisation Based on Background Information. |
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Miscellaneous |
| Year |
2001 |
Publication |
Proceeding ICIP 2001, IEEE International Conference on Image Processing |
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ICIP 2001 |
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1 |
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874–877 |
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Grecia. |
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ADAS;DAG;CIC |
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no |
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ADAS @ adas @ VLP2001 |
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167 |
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| Author |
Robert Benavente; M.C. Olive; Maria Vanrell; Ramon Baldrich |
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| Title |
Colour Perception: A Simple Method for Colour Naming. |
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Miscellaneous |
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1999 |
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Girona |
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CAT @ cat @ BOV1999 |
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47 |
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| Author |
Ivet Rafegas; Maria Vanrell |
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| Title |
Colour Visual Coding in trained Deep Neural Networks |
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2016 |
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European Conference on Visual Perception |
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Barcelona; Spain; August 2016 |
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ECVP |
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CIC |
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no |
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Admin @ si @ RaV2016b |
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2895 |
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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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2010 |
Publication |
Proceedings of The CREATE 2010 Conference |
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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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CAT @ cat @ MOV2010b |
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1308 |
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| Author |
Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich |
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| Title |
DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition |
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Conference Article |
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2015 |
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Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II |
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9475 |
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463-473 |
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| Keywords |
Projector-camera systems; Feature descriptors; Object recognition |
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| Abstract |
Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection. |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-27862-9 |
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ISVC |
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CIC |
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no |
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Admin @ si @ SMG2015 |
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2736 |
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| Author |
Hassan Ahmed Sial; Ramon Baldrich; Maria Vanrell |
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| Title |
Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects |
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Journal Article |
| Year |
2020 |
Publication |
Journal of the Optical Society of America A |
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JOSA A |
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| Volume |
37 |
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1 |
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1-15 |
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Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues. On the other hand, end-to-end deep learning architectures start to achieve interesting results that we believe could be improved if important physical hints were not ignored. In this work, we present a twofold framework: (a) a flexible generation of images overcoming some classical dataset problems such as larger size jointly with coherent lighting appearance; and (b) a flexible architecture tying physical properties through intrinsic losses. Our proposal is versatile, presents low computation time, and achieves state-of-the-art results. |
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CIC; 600.140; 600.12; 600.118 |
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Admin @ si @ SBV2019 |
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3311 |
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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 |
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TPAMI |
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| Volume |
33 |
Issue |
5 |
Pages |
917-930 |
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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. |
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Los Alamitos; CA; USA; |
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IEEE Computer Society |
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0162-8828 |
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CIC |
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no |
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Admin @ si @ VBW2011 |
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1715 |
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| Author |
C. Alejandro Parraga; Jordi Roca; Maria Vanrell |
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| Title |
Do Basic Colors Influence Chromatic Adaptation? |
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Journal Article |
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2011 |
Publication |
Journal of Vision |
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VSS |
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11 |
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11 |
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85 |
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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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1534-7362 |
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CIC |
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no |
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Admin @ si @ PRV2011 |
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1759 |
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| Author |
Eduard Vazquez; Maria Vanrell |
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| Title |
Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial |
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Miscellaneous |
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2008 |
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V Jornades d’Innovacio Docent (UAB) |
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Bellaterra (Spain) |
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CAT @ cat @ VaV2008 |
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1011 |
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| Author |
Ivet Rafegas; Javier Vazquez; Robert Benavente; Maria Vanrell; Susana Alvarez |
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Enhancing spatio-chromatic representation with more-than-three color coding for image description |
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Journal Article |
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2017 |
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Journal of the Optical Society of America A |
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JOSA A |
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34 |
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5 |
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827-837 |
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Extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose a new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to enhance the fact that the number of channels is adapted to the image content. The higher color complexity an image has, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding using these color pivots as a basis. To evaluate the proposed approach we measure its efficiency in an image categorization task. We show how a generic descriptor improves its performance at the description level when applied on the MTT coding. |
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CIC; 600.087 |
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Admin @ si @ RVB2017 |
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2892 |
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Robert Benavente; Maria Vanrell; Ramon Baldrich |
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| Title |
Estimation of Fuzzy Sets for Computational Colour Categorization |
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2004 |
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Color Research and Application, 29(5):342–353 (IF: 0.739) |
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CAT @ cat @ BVB2004 |
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484 |
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| Author |
Francesc Tous; Maria Vanrell; Ramon Baldrich |
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Exploring Colour Constancy Solutions. |
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Miscellaneous |
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2004 |
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CGIV 2004 Second European Conference on Colour in Graphics, Imaging, and Vision, 24:29 |
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Aachen (Germany) |
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CIC |
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CAT @ cat @ TVB2004 |
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452 |
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Maria Vanrell |
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Exploring the space of behaviour of a texture perception algorithm |
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Report |
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1997 |
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CVC Technical Report #12 |
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CVC (UAB) |
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CAT @ cat @ Van1997 |
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523 |
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