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| Author | Jordi Roca; Maria Vanrell; C. Alejandro Parraga | ||||
| Title | What is constant in colour constancy? | Type | Conference Article | ||
| Year | 2012 | Publication | 6th European Conference on Colour in Graphics, Imaging and Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 337-343 | ||
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| Abstract | Color constancy refers to the ability of the human visual system to stabilize
the color appearance of surfaces under an illuminant change. In this work we studied how the interrelations among nine colors are perceived under illuminant changes, particularly whether they remain stable across 10 different conditions (5 illuminants and 2 backgrounds). To do so we have used a paradigm that measures several colors under an immersive state of adaptation. From our measures we defined a perceptual structure descriptor that is up to 87% stable over all conditions, suggesting that color category features could be used to predict color constancy. This is in agreement with previous results on the stability of border categories [1,2] and with computational color constancy algorithms [3] for estimating the scene illuminant. |
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| ISSN | ISBN | 9781622767014 | Medium | ||
| Area | Expedition | Conference  |
CGIV | ||
| Notes | CIC | Approved | no | ||
| Call Number | RVP2012 | Serial | 2189 | ||
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| Author | Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich | ||||
| Title | Perception Based Representations for Computational Colour | Type | Conference Article | ||
| Year | 2011 | Publication | 3rd International Workshop on Computational Color Imaging | Abbreviated Journal | |
| Volume | 6626 | Issue | Pages | 16-30 | |
| Keywords | colour perception, induction, naming, psychophysical data, saliency, segmentation | ||||
| Abstract | The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. | ||||
| Address | Milan, Italy | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | Raimondo Schettini, Shoji Tominaga, Alain Trémeau | |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-642-20403-6 | Medium | ||
| Area | Expedition | Conference |
CCIW | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ VMB2011 | Serial | 1733 | ||
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| Author | Sagnik Das; Hassan Ahmed Sial; Ke Ma; Ramon Baldrich; Maria Vanrell; Dimitris Samaras | ||||
| Title | Intrinsic Decomposition of Document Images In-the-Wild | Type | Conference Article | ||
| Year | 2020 | Publication | 31st British Machine Vision Conference | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Automatic document content processing is affected by artifacts caused by the shape
of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on real data are impossible due to the large amount of data needed. Hence, the current state of the art deep learning models are trained on fully or partially synthetic images. However, document shadow or shading removal results still suffer because: (a) prior methods rely on uniformity of local color statistics, which limit their application on real-scenarios with complex document shapes and textures and; (b) synthetic or hybrid datasets with non-realistic, simulated lighting conditions are used to train the models. In this paper we tackle these problems with our two main contributions. First, a physically constrained learning-based method that directly estimates document reflectance based on intrinsic image formation which generalizes to challenging illumination conditions. Second, a new dataset that clearly improves previous synthetic ones, by adding a large range of realistic shading and diverse multi-illuminant conditions, uniquely customized to deal with documents in-the-wild. The proposed architecture works in two steps. First, a white balancing module neutralizes the color of the illumination on the input image. Based on the proposed multi-illuminant dataset we achieve a good white-balancing in really difficult conditions. Second, the shading separation module accurately disentangles the shading and paper material in a self-supervised manner where only the synthetic texture is used as a weak training signal (obviating the need for very costly ground truth with disentangled versions of shading and reflectance). The proposed approach leads to significant generalization of document reflectance estimation in real scenes with challenging illumination. We extensively evaluate on the real benchmark datasets available for intrinsic image decomposition and document shadow removal tasks. Our reflectance estimation scheme, when used as a pre-processing step of an OCR pipeline, shows a 21% improvement of character error rate (CER), thus, proving the practical applicability. The data and code will be available at: https://github.com/cvlab-stonybrook/DocIIW. |
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| Address | Virtual; September 2020 | ||||
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BMVC | ||
| Notes | CIC; 600.087; 600.140; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ DSM2020 | Serial | 3461 | ||
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| Author | Javier Vazquez; Robert Benavente; Maria Vanrell | ||||
| Title | Naming constraints constancy | Type | Conference Article | ||
| Year | 2012 | Publication | 2nd Joint AVA / BMVA Meeting on Biological and Machine Vision | Abbreviated Journal | |
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| Abstract | Different studies have shown that languages from industrialized cultures
share a set of 11 basic colour terms: red, green, blue, yellow, pink, purple, brown, orange, black, white, and grey (Berlin & Kay, 1969, Basic Color Terms, University of California Press)( Kay & Regier, 2003, PNAS, 100, 9085-9089). Some of these studies have also reported the best representatives or focal values of each colour (Boynton and Olson, 1990, Vision Res. 30,1311–1317), (Sturges and Whitfield, 1995, CRA, 20:6, 364–376). Some further studies have provided us with fuzzy datasets for color naming by asking human observers to rate colours in terms of membership values (Benavente -et al-, 2006, CRA. 31:1, 48–56,). Recently, a computational model based on these human ratings has been developed (Benavente -et al-, 2008, JOSA-A, 25:10, 2582-2593). This computational model follows a fuzzy approach to assign a colour name to a particular RGB value. For example, a pixel with a value (255,0,0) will be named 'red' with membership 1, while a cyan pixel with a RGB value of (0, 200, 200) will be considered to be 0.5 green and 0.5 blue. In this work, we show how this colour naming paradigm can be applied to different computer vision tasks. In particular, we report results in colour constancy (Vazquez-Corral -et al-, 2012, IEEE TIP, in press) showing that the classical constraints on either illumination or surface reflectance can be substituted by the statistical properties encoded in the colour names. [Supported by projects TIN2010-21771-C02-1, CSD2007-00018]. |
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AV A | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ VBV2012 | Serial | 2131 | ||
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| Author | Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva | ||||
| Title | Multiresolution colour texture representations for tile classification | Type | Miscellaneous | ||
| Year | 1999 | Publication | Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes | Abbreviated Journal | |
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| Address | Bilbao | ||||
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| Notes | ADAS;CIC | Approved | no | ||
| Call Number | ADAS @ adas @ LBV1999a | Serial | 3 | ||
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| Author | Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva | ||||
| Title | Visual behaviours for binocular navigation with autonomous systems. | Type | Miscellaneous | ||
| Year | 1999 | Publication | Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes | Abbreviated Journal | |
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| Address | Bilbao | ||||
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RVV1999a | Serial | 13 | ||
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| Author | Maria Vanrell; Jordi Vitria; Xavier Roca | ||||
| Title | A multidimensional scaling approach to explore the behavior of a texture perception algorithm. | Type | Journal Article | ||
| Year | 1997 | Publication | Machine Vision and Applications | Abbreviated Journal | |
| Volume | 9 | Issue | Pages | 262–271 | |
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ VVR1997 | Serial | 35 | ||
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| Author | Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva | ||||
| Title | Gaze control in a binocular robot systems | Type | Miscellaneous | ||
| Year | 1999 | Publication | Abbreviated Journal | ||
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| Address | Barcelona | ||||
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RVV1999b | Serial | 41 | ||
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| Author | Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva | ||||
| Title | Multiresolution texture classification of ceramic tiles. | Type | Book Chapter | ||
| Year | 1999 | Publication | Recent Research developments in optical engineering, Research Signpost, 2: 213–228 | Abbreviated Journal | |
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| Address | India | ||||
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| Notes | ADAS;CIC | Approved | no | ||
| Call Number | ADAS @ adas @ LBV1999b | Serial | 45 | ||
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| Author | Robert Benavente; M.C. Olive; Maria Vanrell; Ramon Baldrich | ||||
| Title | Colour Perception: A Simple Method for Colour Naming. | Type | Miscellaneous | ||
| Year | 1999 | Publication | Abbreviated Journal | ||
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| Address | Girona | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ BOV1999 | Serial | 47 | ||
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| Author | Robert Benavente; Maria Vanrell | ||||
| Title | A colour naming experiment | Type | Report | ||
| Year | 2001 | Publication | CVC Technical Report #56 | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ BeV2001 | Serial | 78 | ||
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| Author | Felipe Lumbreras; Joan Serrat; Ramon Baldrich; Maria Vanrell; Juan J. Villanueva | ||||
| Title | Color Texture Recognition Through Multiresolution Features | Type | Miscellaneous | ||
| Year | 2001 | Publication | QCAV 2001 International Conference on Quality Control by Artificial Vision, France, 1:114–121. | Abbreviated Journal | |
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| Notes | ADAS;CIC | Approved | no | ||
| Call Number | ADAS @ adas @ LSB2001 | Serial | 124 | ||
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| Author | Maria Vanrell; Jordi Vitria; Xavier Roca | ||||
| Title | A General Morphological Framework for Perceptual Texture Discrimination based on Granulometries. | Type | Miscellaneous | ||
| Year | 1993 | Publication | Technical Workshop on Mathematical Morphology and its Applications to Signal Processing. | Abbreviated Journal | |
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| Address | Barcelona | ||||
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| Notes | OR;ISE;CIC;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ VVR1993 | Serial | 154 | ||
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| Author | Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva | ||||
| Title | Colour Normalisation Based on Background Information. | Type | Miscellaneous | ||
| Year | 2001 | Publication | Proceeding ICIP 2001, IEEE International Conference on Image Processing | Abbreviated Journal | ICIP 2001 |
| Volume | Issue | 1 | Pages | 874–877 | |
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| Address | Grecia. | ||||
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| Notes | ADAS;DAG;CIC | Approved | no | ||
| Call Number | ADAS @ adas @ VLP2001 | Serial | 167 | ||
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