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Author |
Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title |
Textual Descriptions for Browsing People by Visual Apperance. |
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Book Chapter |
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Year |
2002 |
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Lecture Notes in Artificial Intelligence |
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2504 |
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419-429 |
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This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building |
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Springer Verlag |
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CAT @ cat @ TBB2002b |
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319 |
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Author |
Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title |
Textual Descriptors for browsing people by visual appearence. |
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Conference Article |
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2002 |
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5è. Congrés Català d’Intel·ligència Artificial CCIA |
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Image retrieval, textual descriptors, colour naming, colour normalization, graph matching. |
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Abstract |
This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building. |
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CAT @ cat @ TBB2002a |
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287 |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title |
Top-Down Color Attention for Object Recognition |
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2009 |
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12th International Conference on Computer Vision |
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979 - 986 |
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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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Kyoto, Japan |
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1550-5499 |
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978-1-4244-4420-5 |
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ICCV |
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CAT @ cat @ SWV2009 |
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1196 |
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Author |
Anna Salvatella; Maria Vanrell; Juan J. Villanueva |
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Title |
Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis |
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2003 |
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3rd International Workshop on Texture Synthesis and Analysis, |
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77–82 |
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Nice |
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1-904410-11-1 |
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CAT @ cat @ SVV2003 |
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422 |
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Anna Salvatella; Maria Vanrell; Ramon Baldrich |
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Subtexture Components for Texture Description |
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Miscellaneous |
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2003 |
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Lecture Notes in Computer Science, vol 2652, pp 884–892 |
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Springer-Verlag |
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CAT @ cat @ SVR2003 |
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421 |
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Anna Salvatella; Maria Vanrell |
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Towards a texture representation database |
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2002 |
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CVC Technical Report #60 |
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CAT @ cat @ SaV2002 |
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526 |
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Author |
C. Alejandro Parraga; Javier Vazquez; Maria Vanrell |
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Title |
A new cone activation-based natural images dataset |
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Journal Article |
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2009 |
Publication |
Perception |
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PER |
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36 |
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180 |
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We generated a new dataset of digital natural images where each colour plane corresponds to the human LMS (long-, medium-, short-wavelength) cone activations. The images were chosen to represent five different visual environments (eg forest, seaside, mountain snow, urban, motorways) and were taken under natural illumination at different times of day. At the bottom-left corner of each picture there was a matte grey ball of approximately constant spectral reflectance (across the camera's response spectrum,) and nearly Lambertian reflective properties, which allows to compute (and remove, if necessary) the illuminant's colour and intensity. The camera (Sigma Foveon SD10) was calibrated by measuring its sensor's spectral responses using a set of 31 spectrally narrowband interference filters. This allowed conversion of the final camera-dependent RGB colour space into the Smith and Pokorny (1975) cone activation space by means of a polynomial transformation, optimised for a set of 1269 Munsell chip reflectances. This new method is an improvement over the usual 3 × 3 matrix transformation which is only accurate for spectrally-narrowband colours. The camera-to-LMS transformation can be recalculated to consider other non-human visual systems. The dataset is available to download from our website. |
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CAT @ cat @ PVV2009 |
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1193 |
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Author |
Olivier Penacchio; C. Alejandro Parraga; Maria Vanrell |
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Title |
Natural Scene Statistics account for Human Cones Ratios |
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2010 |
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Perception. ECVP Abstract Supplement |
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PER |
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39 |
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101 |
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In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we completed our parametric fuzzy-sets model of colour naming space. |
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CAT @ cat @ PPV2010 |
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1357 |
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C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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Towards a general model of colour categorization which considers context |
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2010 |
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Perception. ECVP Abstract Supplement |
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PER |
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39 |
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86 |
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In two previous experiments [Parraga et al, 2009 J. of Im. Sci. and Tech 53(3) 031106; Benavente et al,2009 Perception 38 ECVP Supplement, 36] the boundaries of basic colour categories were measured.
In the first experiment, samples were presented in isolation (ie on a dark background) and boundaries were measured using a yes/no paradigm. In the second, subjects adjusted the chromaticity of a sample presented on a random Mondrian background to find the boundary between pairs of adjacent colours.
Results from these experiments showed significant di erences but it was not possible to conclude whether this discrepancy was due to the absence/presence of a colourful background or to the di erences in the paradigms used. In this work, we settle this question by repeating the first experiment (ie samples presented on a dark background) using the second paradigm. A comparison of results shows that
although boundary locations are very similar, boundaries measured in context are significantly di erent(more di use) than those measured in isolation (confirmed by a Student’s t-test analysis on the subject’s answers statistical distributions). In addition, we completed the mapping of colour name space by measuring the boundaries between chromatic colours and the achromatic centre. With these results we
completed our parametric fuzzy-sets model of colour naming space. |
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CAT @ cat @ PBV2010b |
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1326 |
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Author |
C. Alejandro Parraga; Ramon Baldrich; Maria Vanrell |
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Title |
Accurate Mapping of Natural Scenes Radiance to Cone Activation Space: A New Image Dataset |
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Conference Article |
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2010 |
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5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science |
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50–57 |
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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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Joensuu, Finland |
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9781617388897 |
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CGIV/MCS |
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CAT @ cat @ PBV2010a |
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1322 |
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C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Title |
Psychophysical measurements to model inter-colour regions of colour-naming space |
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Journal Article |
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2009 |
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Journal of Imaging Science and Technology |
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53 |
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3 |
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031106 (8 pages) |
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image processing; Analysis |
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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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CAT @ cat @ PBV2009 |
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1157 |
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C. Alejandro Parraga; Robert Benavente; Maria Vanrell; Ramon Baldrich |
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Modelling Inter-Colour Regions of Colour Naming Space |
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2008 |
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4th European Conference on Colour in Graphics, Imaging and Vision Proceedings |
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218–222 |
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Terrassa (Spain) |
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CGIV08 |
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CAT @ cat @ PBV2008 |
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969 |
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C. Alejandro Parraga; Robert Benavente; Maria Vanrell |
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Modeling Colour-Naming Space with Fuzzy Sets |
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2007 |
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Perception 36:198–198, supp |
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CAT @ cat @ PBV2007 |
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843 |
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Xavier Otazu; Maria Vanrell; C. Alejandro Parraga |
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Colour induction effects are modelled by a low-level multiresolution wavelet framework |
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2008 |
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Perception 37(Suppl.): 107 |
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CIC |
Approved |
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CAT @ cat @ OVP2008b |
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1055 |
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