Partha Pratim Roy, Eduard Vazquez, Josep Llados, Ramon Baldrich, & Umapada Pal. (2008). A System to Segment Text and Symbols from Color Maps. In Graphics Recognition. Recent Advances and New Opportunities (Vol. 5046, pp. 245–256). LNCS.
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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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Eduard Vazquez, Joost Van de Weijer, & Ramon Baldrich. (2008). Image Segmentation in the Presence of Shadows and Highligts. In 10th European Conference on Computer Vision (Vol. 5305, 1–14). LNCS.
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Agata Lapedriza, Jaume Garcia, Ernest Valveny, Robert Benavente, Miquel Ferrer, & Gemma Sanchez. (2008). Una experiencia de aprenentatge basada en projectes en el ambit de la informatica.
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Robert Benavente, Ernest Valveny, Jaume Garcia, Agata Lapedriza, Miquel Ferrer, & Gemma Sanchez. (2008). Una experiencia de adaptacion al EEES de las asignaturas de programacion en Ingenieria Informatica.
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Jose Manuel Alvarez, Antonio Lopez, & Ramon Baldrich. (2008). Illuminant Invariant Model-Based Road Segmentation. In IEEE Intelligent Vehicles Symposium, (1155–1180).
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T. Widemann, & Xavier Otazu. (2009). Titanias radius and an upper limit on its atmosphere from the September 8, 2001 stellar occultation. International Journal of Solar System Studies, 199(2), 458–476.
Abstract: On September 8, 2001 around 2 h UT, the largest uranian moon, Titania, occulted Hipparcos star 106829 (alias SAO 164538, a V=7.2, K0 III star). This was the first-ever observed occultation by this satellite, a rare event as Titania subtends only 0.11 arcsec on the sky. The star's unusual brightness allowed many observers, both amateurs or professionals, to monitor this unique event, providing fifty-seven occultations chords over three continents, all reported here. Selecting the best 27 occultation chords, and assuming a circular limb, we derive Titania's radius: View the MathML source (1-σ error bar). This implies a density of View the MathML source using the value View the MathML source derived by Taylor [Taylor, D.B., 1998. Astron. Astrophys. 330, 362–374]. We do not detect any significant difference between equatorial and polar radii, in the limit View the MathML source, in agreement with Voyager limb image retrieval during the 1986 flyby. Titania's offset with respect to the DE405 + URA027 (based on GUST86 theory) ephemeris is derived: ΔαTcos(δT)=−108±13 mas and ΔδT=−62±7 mas (ICRF J2000.0 system). Most of this offset is attributable to a Uranus' barycentric offset with respect to DE405, that we estimate to be: View the MathML source and ΔδU=−85±25 mas at the moment of occultation. This offset is confirmed by another Titania stellar occultation observed on August 1st, 2003, which provides an offset of ΔαTcos(δT)=−127±20 mas and ΔδT=−97±13 mas for the satellite. The combined ingress and egress data do not show any significant hint for atmospheric refraction, allowing us to set surface pressure limits at the level of 10–20 nbar. More specifically, we find an upper limit of 13 nbar (1-σ level) at 70 K and 17 nbar at 80 K, for a putative isothermal CO2 atmosphere. We also provide an upper limit of 8 nbar for a possible CH4 atmosphere, and 22 nbar for pure N2, again at the 1-σ level. We finally constrain the stellar size using the time-resolved star disappearance and reappearance at ingress and egress. We find an angular diameter of 0.54±0.03 mas (corresponding to View the MathML source projected at Titania). With a distance of 170±25 parsecs, this corresponds to a radius of 9.8±0.2 solar radii for HIP 106829, typical of a K0 III giant.
Keywords: Occultations; Uranus, satellites; Satellites, shapes; Satellites, dynamics; Ices; Satellites, atmospheres
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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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Antonio Lopez, J. Hilgenstock, A. Busse, Ramon Baldrich, Felipe Lumbreras, & Joan Serrat. (2008). Nightime Vehicle Detecion for Intelligent Headlight Control. In Advanced Concepts for Intelligent Vision Systems, 10th International Conference, Proceedings, (Vol. 5259, 113–124). LNCS.
Keywords: Intelligent Headlights; vehicle detection
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Robert Benavente. (2007). A Parametric Model for Computational Colour Naming (Maria Vanrell, Ed.). Ph.D. thesis, Ediciones Graficas Rey, .
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Robert Benavente, Laura Igual, & Fernando Vilariño. (2008). Current Challenges in Computer Vision.
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Antonio Lopez, J. Hilgenstock, A. Busse, Ramon Baldrich, Felipe Lumbreras, & Joan Serrat. (2008). Temporal Coherence Analysis for Intelligent Headlight Control.
Keywords: Intelligent Headlights
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C. Alejandro Parraga, Robert Benavente, Maria Vanrell, & Ramon Baldrich. (2009). Psychophysical measurements to model inter-colour regions of colour-naming space. Journal of Imaging Science and Technology, 53(3), 031106 (8 pages).
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.
Keywords: image processing; Analysis
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Javier Vazquez, C. Alejandro Parraga, Maria Vanrell, & Ramon Baldrich. (2009). Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset. Journal of Imaging Science and Technology, 53(3), 031105–9.
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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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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Josep M. Gonfaus, Xavier Boix, Joost Van de Weijer, Andrew Bagdanov, Joan Serrat, & Jordi Gonzalez. (2010). Harmony Potentials for Joint Classification and Segmentation. In 23rd IEEE Conference on Computer Vision and Pattern Recognition (3280–3287).
Abstract: Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within one region. This simplified model especially limits the impact that observations at larger scales may have on the CRF model. Neglecting the information at larger scales is undesirable since class-label estimates based on these scales are more reliable than at smaller, noisier scales. To address this problem, we propose a new potential, called harmony potential, which can encode any possible combination of class labels. We propose an effective sampling strategy that renders tractable the underlying optimization problem. Results show that our approach obtains state-of-the-art results on two challenging datasets: Pascal VOC 2009 and MSRC-21.
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Naila Murray, & Eduard Vazquez. (2010). Lacuna Restoration: How to choose a neutral colour? In Proceedings of The CREATE 2010 Conference (248–252).
Abstract: Painting restoration which involves filling in material loss (called lacuna) is a complex process. Several standard techniques exist to tackle lacuna restoration,
and this article focuses on those techniques that employ a “neutral” colour to mask the defect. Restoration experts often disagree on the choice of such a colour and in fact, the concept of a neutral colour is controversial. We posit that a neutral colour is one that attracts relatively little visual attention for a specific lacuna. We conducted an eye tracking experiment to compare two common neutral
colour selection methods, specifically the most common local colour and the mean local colour. Results obtained demonstrate that the most common local colour triggers less visual attention in general. Notwithstanding, we have observed instances in which the most common colour triggers a significant amount of attention when subjects spent time resolving their confusion about whether or not a lacuna was part of the painting.
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Eduard Vazquez, & Ramon Baldrich. (2010). Non-supervised goodness measure for image segmentation. In Proceedings of The CREATE 2010 Conference (334–335).
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