| Home | << 1 2 3 4 5 6 7 8 >> |
|
| Records | Links | |||||
|---|---|---|---|---|---|---|
| Author | Olivier Penacchio; C. Alejandro Parraga; Maria Vanrell |
 |
||||
| Title | Natural Scene Statistics account for Human Cones Ratios | Type | Journal Article | |||
| Year | 2010 | Publication | Perception. ECVP Abstract Supplement | Abbreviated Journal | PER | |
Volume  |
39 | Issue | Pages | 101 | ||
| Keywords | ||||||
| Abstract | 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. |
|||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ PPV2010 | Serial | 1357 | |||
| Permanent link to this record | ||||||
| Author | C. Alejandro Parraga; Olivier Penacchio; Maria Vanrell |
|
||||
| Title | Retinal Filtering Matches Natural Image Statistics at Low Luminance Levels | Type | Journal Article | |||
| Year | 2011 | Publication | Perception | Abbreviated Journal | PER | |
| Volume |
40 | Issue | Pages | 96 | ||
| Keywords | ||||||
| Abstract | The assumption that the retina’s main objective is to provide a minimum entropy representation to higher visual areas (ie efficient coding principle) allows to predict retinal filtering in space–time and colour (Atick, 1992 Network 3 213–251). This is achieved by considering the power spectra of natural images (which is proportional to 1/f2) and the suppression of retinal and image noise. However, most studies consider images within a limited range of lighting conditions (eg near noon) whereas the visual system’s spatial filtering depends on light intensity and the spatiochromatic properties of natural scenes depend of the time of the day. Here, we explore whether the dependence of visual spatial filtering on luminance match the changes in power spectrum of natural scenes at different times of the day. Using human cone-activation based naturalistic stimuli (from the Barcelona Calibrated Images Database), we show that for a range of luminance levels, the shape of the retinal CSF reflects the slope of the power spectrum at low spatial frequencies. Accordingly, the retina implements the filtering which best decorrelates the input signal at every luminance level. This result is in line with the body of work that places efficient coding as a guiding neural principle. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ PPV2011 | Serial | 1720 | |||
| Permanent link to this record | ||||||
| Author | Jordi Roca; C. Alejandro Parraga; Maria Vanrell |
 
|
||||
| Title | Predicting categorical colour perception in successive colour constancy | Type | Abstract | |||
| Year | 2012 | Publication | Perception | Abbreviated Journal | PER | |
| Volume |
41 | Issue | Pages | 138 | ||
| Keywords | ||||||
| Abstract | Colour constancy is a perceptual mechanism that seeks to keep the colour of objects relatively stable under an illumination shift. Experiments haveshown that its effects depend on the number of colours present in the scene. We
studied categorical colour changes under different adaptation states, in particular, whether the colour categories seen under a chromatically neutral illuminant are the same after a shift in the chromaticity of the illumination. To do this, we developed the chromatic setting paradigm (2011 Journal of Vision11 349), which is as an extension of achromatic setting to colour categories. The paradigm exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. Our experiments were run on a CRT monitor (inside a dark room) under various simulated illuminants and restricting the number of colours of the Mondrian background to three, thus weakening the adaptation effect. Our results show a change in the colour categories present before (under neutral illumination) and after adaptation (under coloured illuminants) with a tendency for adapted colours to be less saturated than before adaptation. This behaviour was predicted by a simple affine matrix model, adjusted to the chromatic setting results. |
|||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 0301-0066 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ RPV2012 | Serial | 2188 | |||
| Permanent link to this record | ||||||
| Author | Susana Alvarez; Maria Vanrell |
|
||||
| Title | Texton theory revisited: a bag-of-words approach to combine textons | Type | Journal Article | |||
| Year | 2012 | Publication | Pattern Recognition | Abbreviated Journal | PR | |
| Volume |
45 | Issue | 12 | Pages | 4312-4325 | |
| Keywords | ||||||
| Abstract | The aim of this paper is to revisit an old theory of texture perception and
update its computational implementation by extending it to colour. With this in mind we try to capture the optimality of perceptual systems. This is achieved in the proposed approach by sharing well-known early stages of the visual processes and extracting low-dimensional features that perfectly encode adequate properties for a large variety of textures without needing further learning stages. We propose several descriptors in a bag-of-words framework that are derived from different quantisation models on to the feature spaces. Our perceptual features are directly given by the shape and colour attributes of image blobs, which are the textons. In this way we avoid learning visual words and directly build the vocabularies on these lowdimensionaltexton spaces. Main differences between proposed descriptors rely on how co-occurrence of blob attributes is represented in the vocabularies. Our approach overcomes current state-of-art in colour texture description which is proved in several experiments on large texture datasets. |
|||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 0031-3203 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ AlV2012a | Serial | 2130 | |||
| Permanent link to this record | ||||||
| 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 | |
| Keywords | ||||||
| Abstract | ||||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ OVP2008a | Serial | 927 | |||
| Permanent link to this record | ||||||
| Author | Abel Gonzalez-Garcia; Robert Benavente; Olivier Penacchio; Javier Vazquez; Maria Vanrell; C. Alejandro Parraga |
|
||||
| Title | Coloresia: An Interactive Colour Perception Device for the Visually Impaired | Type | Book Chapter | |||
| Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | ||
| Volume |
48 | Issue | Pages | 47-66 | ||
| Keywords | ||||||
| Abstract | A significative percentage of the human population suffer from impairments in their capacity to distinguish or even see colours. For them, everyday tasks like navigating through a train or metro network map becomes demanding. We present a novel technique for extracting colour information from everyday natural stimuli and presenting it to visually impaired users as pleasant, non-invasive sound. This technique was implemented inside a Personal Digital Assistant (PDA) portable device. In this implementation, colour information is extracted from the input image and categorised according to how human observers segment the colour space. This information is subsequently converted into sound and sent to the user via speakers or headphones. In the original implementation, it is possible for the user to send its feedback to reconfigure the system, however several features such as these were not implemented because the current technology is limited.We are confident that the full implementation will be possible in the near future as PDA technology improves. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | ||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.052; 605.203 | Approved | no | |||
| Call Number | Admin @ si @ GBP2013 | Serial | 2266 | |||
| Permanent link to this record | ||||||
| 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. |
|||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ PBV2009 | Serial | 1157 | |||
| Permanent link to this record | ||||||
| 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 | |
| Keywords | ||||||
| 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. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ VPV2009a | Serial | 1171 | |||
| Permanent link to this record | ||||||
| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
|
||||
| Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | |||
| Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV | |
| Volume |
98 | Issue | 1 | Pages | 49-64 | |
| Keywords | ||||||
| Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, 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, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Springer Netherlands | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 0920-5691 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ KWV2012 | Serial | 1864 | |||
| Permanent link to this record | ||||||
| Author | Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
|
||||
| Title | Low-dimensional and Comprehensive Color Texture Description | Type | Journal Article | |||
| Year | 2012 | Publication | Computer Vision and Image Understanding | Abbreviated Journal | CVIU | |
| Volume |
116 | Issue | I | Pages | 54-67 | |
| Keywords | ||||||
| Abstract | Image retrieval can be dealt by combining standard descriptors, such as those of MPEG-7, which are defined independently for each visual cue (e.g. SCD or CLD for Color, HTD for texture or EHD for edges).
A common problem is to combine similarities coming from descriptors representing different concepts in different spaces. In this paper we propose a color texture description that bypasses this problem from its inherent definition. It is based on a low dimensional space with 6 perceptual axes. Texture is described in a 3D space derived from a direct implementation of the original Julesz’s Texton theory and color is described in a 3D perceptual space. This early fusion through the blob concept in these two bounded spaces avoids the problem and allows us to derive a sparse color-texture descriptor that achieves similar performance compared to MPEG-7 in image retrieval. Moreover, our descriptor presents comprehensive qualities since it can also be applied either in segmentation or browsing: (a) a dense image representation is defined from the descriptor showing a reasonable performance in locating texture patterns included in complex images; and (b) a vocabulary of basic terms is derived to build an intermediate level descriptor in natural language improving browsing by bridging semantic gap |
|||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | 1077-3142 | ISBN | Medium | |||
| Area | Expedition | Conference | ||||
| Notes | CAT;CIC | Approved | no | |||
| Call Number | Admin @ si @ ASV2012 | Serial | 1827 | |||
| Permanent link to this record | ||||||
| Author | Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias |
|
||||
| Title | Understanding trained CNNs by indexing neuron selectivity | Type | Journal Article | |||
| Year | 2020 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL | |
| Volume |
136 | Issue | Pages | 318-325 | ||
| Keywords | ||||||
| Abstract | The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understanding of the representations they build and how these representations are organized. To help understanding these issues, we propose to describe the activity of individual neurons by their Neuron Feature visualization and quantify their inherent selectivity with two specific properties. We explore selectivity indexes for: an image feature (color); and an image label (class membership). Our contribution is a framework to seek or classify neurons by indexing on these selectivity properties. It helps to find color selective neurons, such as a red-mushroom neuron in layer Conv4 or class selective neurons such as dog-face neurons in layer Conv5 in VGG-M, and establishes a methodology to derive other selectivity properties. Indexing on neuron selectivity can statistically draw how features and classes are represented through layers in a moment when the size of trained nets is growing and automatic tools to index neurons can be helpful. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.087; 600.140; 600.118 | Approved | no | |||
| Call Number | Admin @ si @ RVL2019 | Serial | 3310 | |||
| Permanent link to this record | ||||||
| Author | Ivet Rafegas; Maria Vanrell |
|
||||
| Title | Color encoding in biologically-inspired convolutional neural networks | Type | Journal Article | |||
| Year | 2018 | Publication | Vision Research | Abbreviated Journal | VR | |
| Volume |
151 | Issue | Pages | 7-17 | ||
| Keywords | Color coding; Computer vision; Deep learning; Convolutional neural networks | |||||
| Abstract | Convolutional Neural Networks have been proposed as suitable frameworks to model biological vision. Some of these artificial networks showed representational properties that rival primate performances in object recognition. In this paper we explore how color is encoded in a trained artificial network. It is performed by estimating a color selectivity index for each neuron, which allows us to describe the neuron activity to a color input stimuli. The index allows us to classify whether they are color selective or not and if they are of a single or double color. We have determined that all five convolutional layers of the network have a large number of color selective neurons. Color opponency clearly emerges in the first layer, presenting 4 main axes (Black-White, Red-Cyan, Blue-Yellow and Magenta-Green), but this is reduced and rotated as we go deeper into the network. In layer 2 we find a denser hue sampling of color neurons and opponency is reduced almost to one new main axis, the Bluish-Orangish coinciding with the dataset bias. In layers 3, 4 and 5 color neurons are similar amongst themselves, presenting different type of neurons that detect specific colored objects (e.g., orangish faces), specific surrounds (e.g., blue sky) or specific colored or contrasted object-surround configurations (e.g. blue blob in a green surround). Overall, our work concludes that color and shape representation are successively entangled through all the layers of the studied network, revealing certain parallelisms with the reported evidences in primate brains that can provide useful insight into intermediate hierarchical spatio-chromatic representations. | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | CIC; 600.051; 600.087 | Approved | no | |||
| Call Number | Admin @ si @RaV2018 | Serial | 3114 | |||
| Permanent link to this record | ||||||
| Author | Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
|
||||
| Title | Textual Descriptions for Browsing People by Visual Apperance. | Type | Book Chapter | |||
| Year | 2002 | Publication | Lecture Notes in Artificial Intelligence | Abbreviated Journal | ||
| Volume |
2504 | Issue | Pages | 419-429 | ||
| Keywords | ||||||
| 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 | |||||
| Address | ||||||
| Corporate Author | Thesis | |||||
| Publisher | Springer Verlag | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | ||||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | ||||
| Notes | DAG;CIC | Approved | no | |||
| Call Number | CAT @ cat @ TBB2002b | Serial | 319 | |||
| Permanent link to this record | ||||||
| Author | Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell |
|
||||
| Title | High-Level Clothes Description Based on Colour-Texture and Structural Features | Type | Conference Article | |||
| Year | 2003 | Publication | 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003 | Abbreviated Journal | ||
| Volume |
2652 | Issue | Pages | 108-116 | ||
| Keywords | ||||||
| Abstract | ecture Notes in Computer Science 2652 108–116 | |||||
| Address | Palma de Mallorca | |||||
| Corporate Author | Thesis | |||||
| Publisher | Place of Publication | Editor | ||||
| Language | Summary Language | Original Title | ||||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
| Series Volume | Series Issue | Edition | ||||
| ISSN | ISBN | Medium | ||||
| Area | Expedition | Conference | IbPRIA | |||
| Notes | DAG;CIC | Approved | no | |||
| Call Number | CAT @ cat @ BTL2003b | Serial | 369 | |||
| Permanent link to this record | ||||||