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Ivet Rafegas, & Maria Vanrell. (2016). Colour Visual Coding in trained Deep Neural Networks. In European Conference on Visual Perception.
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Christophe Rigaud, Dimosthenis Karatzas, Joost Van de Weijer, Jean-Christophe Burie, & Jean-Marc Ogier. (2013). Automatic text localisation in scanned comic books. In Proceedings of the International Conference on Computer Vision Theory and Applications (pp. 814–819).
Abstract: Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented.
Keywords: Text localization; comics; text/graphic separation; complex background; unstructured document
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Robert Benavente, Gemma Sanchez, Ramon Baldrich, Maria Vanrell, & Josep Llados. (2000). Normalized colour segmentation for human appearance description. In 15 th International Conference on Pattern Recognition (Vol. 3, pp. 637–641).
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Xavier Roca, Jordi Vitria, Maria Vanrell, & Juan J. Villanueva. (1999). Gaze control in a binocular robot systems.
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Maria Vanrell, Jordi Vitria, & Xavier Roca. (1993). A General Morphological Framework for Perceptual Texture Discrimination based on Granulometries..
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Ramon Baldrich, Maria Vanrell, Robert Benavente, & Anna Salvatella. (2003). Color Enhancement based on perceptual sharpening.
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Shida Beigpour, & Joost Van de Weijer. (2011). Object Recoloring Based on Intrinsic Image Estimation. In 13th IEEE International Conference in Computer Vision (pp. 327–334).
Abstract: Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods.
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Shida Beigpour. (2013). Illumination and object reflectance modeling (Joost Van de Weijer, & Ernest Valveny, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: More realistic and accurate models of the scene illumination and object reflectance can greatly improve the quality of many computer vision and computer graphics tasks. Using such model, a more profound knowledge about the interaction of light with object surfaces can be established which proves crucial to a variety of computer vision applications. In the current work, we investigate the various existing approaches to illumination and reflectance modeling and form an analysis on their shortcomings in capturing the complexity of real-world scenes. Based on this analysis we propose improvements to different aspects of reflectance and illumination estimation in order to more realistically model the real-world scenes in the presence of complex lighting phenomena (i.e, multiple illuminants, interreflections and shadows). Moreover, we captured our own multi-illuminant dataset which consists of complex scenes and illumination conditions both outdoor and in laboratory conditions. In addition we investigate the use of synthetic data to facilitate the construction of datasets and improve the process of obtaining ground-truth information.
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Robert Benavente, C. Alejandro Parraga, & Maria Vanrell. (2010). La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas. In 9th Congreso Nacional del Color (92–95).
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.
Keywords: Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos
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Joost Van de Weijer, & Shida Beigpour. (2011). The Dichromatic Reflection Model: Future Research Directions and Applications. In José L. and B. Mestetskiy (Ed.), International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SciTePress.
Abstract: The dichromatic reflection model (DRM) predicts that color distributions form a parallelogram in color space, whose shape is defined by the body reflectance and the illuminant color. In this paper we resume the assumptions which led to the DRM and shortly recall two of its main applications domains: color image segmentation and photometric invariant feature computation. After having introduced the model we discuss several limitations of the theory, especially those which are raised once working on real-world uncalibrated images. In addition, we summerize recent extensions of the model which allow to handle more complicated light interactions. Finally, we suggest some future research directions which would further extend its applicability.
Keywords: dblp
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Robert Benavente, & Maria Vanrell. (2004). Fuzzy Colour Naming Based on Sigmoid Membership Functions..
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Xavier Otazu, & Maria Vanrell. (2004). Building Perceived Colour Images..
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Francesc Tous, Maria Vanrell, & Ramon Baldrich. (2004). Exploring Colour Constancy Solutions..
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Maria Vanrell, Jordi Vitria, & Xavier Roca. (1997). A multidimensional scaling approach to explore the behavior of a texture perception algorithm. Machine Vision and Applications, 9, 262–271.
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Ramon Baldrich. (2001). Perceptual approach to a computational colour-texture representation for surface inspection..
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Felipe Lumbreras, Joan Serrat, Ramon Baldrich, Maria Vanrell, & Juan J. Villanueva. (2001). Color Texture Recognition Through Multiresolution Features.
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Robert Benavente, Ramon Baldrich, M.C. Olive, & Maria Vanrell. (2000). Colour Naming Considering the Colour Variability Problem..
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Xavier Roca, Jordi Vitria, Maria Vanrell, & Juan J. Villanueva. (2000). Visual behaviours for binocular navigation with autonomous systems..
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