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Eduard Vazquez, Ramon Baldrich, Javier Vazquez, & Maria Vanrell. (2007). Topological histogram reduction towards colour segmentation. In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:55–62.
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Javier Vazquez, Maria Vanrell, Anna Salvatella, & Eduard Vazquez. (2007). A colour space based on the image content. In Artificial Intelligence Research and Development, C. Angulo and L. Godo, pp 205–212 IOS Press.
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Xavier Otazu, Maria Vanrell, & C. Alejandro Parraga. (2007). Mutiresolution Wavelet Framework Reproduces Induction Effects. Perception 36:167–167, supp.
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C. Alejandro Parraga, Robert Benavente, & Maria Vanrell. (2007). Modeling Colour-Naming Space with Fuzzy Sets. Perception 36:198–198, supp.
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Robert Benavente, & Maria Vanrell. (2007). Parametrizacion del Espacio de Categorias de Color.
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Javier Vazquez, Maria Vanrell, & Ramon Baldrich. (2008). Towards a Psychophysical Evaluation of Colour Constancy Algorithms. In 4th European Conference on Colour in Graphics, Imaging and Vision Proceedings (372–377).
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C. Alejandro Parraga, Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2008). Modelling Inter-Colour Regions of Colour Naming Space. In 4th European Conference on Colour in Graphics, Imaging and Vision Proceedings (218–222).
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Eduard Vazquez, & Maria Vanrell. (2008). Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial.
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Xavier Otazu, Maria Vanrell, & C. Alejandro Parraga. (2008). Colour induction effects are modelled by a low-level multiresolution wavelet framework. Perception 37(Suppl.): 107.
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Fahad Shahbaz Khan, Joost Van de Weijer, & Maria Vanrell. (2009). Top-Down Color Attention for Object Recognition. In 12th International Conference on Computer Vision (pp. 979–986).
Abstract: Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information.
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Jaime Moreno, Xavier Otazu, & Maria Vanrell. (2010). Local Perceptual Weighting in JPEG2000 for Color Images. In 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science (255–260).
Abstract: 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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Jaime Moreno, Xavier Otazu, & Maria Vanrell. (2010). Contribution of CIWaM in JPEG2000 Quantization for Color Images. In Proceedings of The CREATE 2010 Conference (132–136).
Abstract: 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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C. Alejandro Parraga, Ramon Baldrich, & Maria Vanrell. (2010). Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset. In 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science (50–57).
Abstract: 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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Javier Vazquez, G. D. Finlayson, & Maria Vanrell. (2010). A compact singularity function to predict WCS data and unique hues. In 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science (33–38).
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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