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Author Fernando Lopez; J.M. Valiente; Ramon Baldrich; Maria Vanrell
Title Fast surface grading using color statistics in the CIELab space Type Conference Article
Year 2005 Publication Pattern Recognition and Image Analysis. IbPRIA 2005 Abbreviated Journal
Volume LNCS 3523 Issue Pages 66-673
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Address Germany
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Area Expedition Conference IbPRIA
Notes (up) CIC Approved no
Call Number CAT @ cat @ LVB2005 Serial 641
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Author Xavier Otazu; Maria Vanrell
Title Several lightness induction effects with a computational multiresolution wavelet framework Type Journal
Year 2006 Publication 29th European Conference on Visual Perception (ECVP’06), Perception Suppl s, 32: 56–56 Abbreviated Journal
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Address Saint-Petersburg (Russia)
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Notes (up) CIC Approved no
Call Number CAT @ cat @ OtV2006 Serial 659
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Author Eduard Vazquez; Francesc Tous; Ramon Baldrich; Maria Vanrell
Title n-Dimensional Distribution Reduction Preserving its Structure Type Book Chapter
Year 2006 Publication Artificial Intelligence Research and Development, M. Polit et al. (Eds.), 146: 167–175 Abbreviated Journal
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Address IOS Press
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Notes (up) CIC Approved no
Call Number CAT @ cat @ VTB2006a Serial 681
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Author Eduard Vazquez; Ramon Baldrich; Javier Vazquez; Maria Vanrell
Title Topological histogram reduction towards colour segmentation Type Book Chapter
Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:55–62 Abbreviated Journal
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Address Gerona (Spain)
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Notes (up) CIC Approved no
Call Number CAT @ cat @ VBV2007 Serial 809
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Author Javier Vazquez; Maria Vanrell; Anna Salvatella; Eduard Vazquez
Title A colour space based on the image content Type Book Chapter
Year 2007 Publication Artificial Intelligence Research and Development, C. Angulo and L. Godo, pp 205–212 IOS Press Abbreviated Journal
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Notes (up) CIC Approved no
Call Number CAT @ cat @ VVS2007 Serial 829
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Author Xavier Otazu; Maria Vanrell; C. Alejandro Parraga
Title Mutiresolution Wavelet Framework Reproduces Induction Effects Type Journal
Year 2007 Publication Perception 36:167–167, supp Abbreviated Journal
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Notes (up) CIC Approved no
Call Number CAT @ cat @ OVP2007 Serial 842
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Author C. Alejandro Parraga; Robert Benavente; Maria Vanrell
Title Modeling Colour-Naming Space with Fuzzy Sets Type Journal
Year 2007 Publication Perception 36:198–198, supp Abbreviated Journal
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Notes (up) CIC Approved no
Call Number CAT @ cat @ PBV2007 Serial 843
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Author Xavier Otazu; Maria Vanrell; C. Alejandro Parraga
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 (up) CIC Approved no
Call Number CAT @ cat @ OVP2008a Serial 927
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Author Robert Benavente; Maria Vanrell; Ramon Baldrich
Title Parametric Fuzzy Sets for Automatic Color Naming Type Journal
Year 2008 Publication Journal of the Optical Society of America A Abbreviated Journal
Volume 25 Issue 10 Pages 2582–2593
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Notes (up) CIC Approved no
Call Number CAT @ cat @ BVB2008 Serial 1004
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Author Eduard Vazquez; Maria Vanrell
Title Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial Type Miscellaneous
Year 2008 Publication V Jornades d’Innovacio Docent (UAB) Abbreviated Journal
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Address Bellaterra (Spain)
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Notes (up) CIC Approved no
Call Number CAT @ cat @ VaV2008 Serial 1011
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Author Xavier Otazu; Maria Vanrell; C. Alejandro Parraga
Title Colour induction effects are modelled by a low-level multiresolution wavelet framework Type Journal
Year 2008 Publication Perception 37(Suppl.): 107 Abbreviated Journal
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Notes (up) CIC Approved no
Call Number CAT @ cat @ OVP2008b Serial 1055
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Author C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich
Title Psychophysical measurements to model inter-colour regions of colour-naming space Type Journal Article
Year 2009 Publication Journal of Imaging Science and Technology Abbreviated Journal
Volume 53 Issue 3 Pages 031106 (8 pages)
Keywords image processing; Analysis
Abstract JCR Impact Factor 2009: 0.391
In this paper, we present a fuzzy-set of parametric functions which segment the CIE lab space into eleven regions which correspond to the group of common universal categories present in all evolved languages as identified by anthropologists and linguists. The set of functions is intended to model a color-name assignment task by humans and differs from other models in its emphasis on the inter-color boundary regions, which were explicitly measured by means of a psychophysics experiment. In our particular implementation, the CIE lab space was segmented into eleven color categories using a Triple Sigmoid as the fuzzy sets basis, whose parameters are included in this paper. The model’s parameters were adjusted according to the psychophysical results of a yes/no discrimination paradigm where observers had to choose (English) names for isoluminant colors belonging to regions in-between neighboring categories. These colors were presented on a calibrated CRT monitor (14-bit x 3 precision). The experimental results show that inter- color boundary regions are much less defined than expected and color samples other than those near the most representatives are needed to define the position and shape of boundaries between categories. The extended set of model parameters is given as a table.
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Notes (up) CIC Approved no
Call Number CAT @ cat @ PBV2009 Serial 1157
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Author Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich
Title Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset Type Journal Article
Year 2009 Publication Journal of Imaging Science and Technology Abbreviated Journal
Volume 53 Issue 3 Pages 031105–9
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Abstract The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene.
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Notes (up) CIC Approved no
Call Number CAT @ cat @ VPV2009a Serial 1171
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Author Javier Vazquez; C. Alejandro Parraga; Maria Vanrell
Title Ordinal pairwise method for natural images comparison Type Journal Article
Year 2009 Publication Perception Abbreviated Journal PER
Volume 38 Issue Pages 180
Keywords
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 (up) CIC Approved no
Call Number CAT @ cat @ VPV2009b Serial 1191
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