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| Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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| Title | Who Painted this Painting? | Type | Conference Article | |||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | ||
| Volume | Issue | Pages  |
329–333 | |||
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| Address | Gjovik (Norway) | |||||
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| Area | Expedition | Conference | CREATE | |||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ KWV2010 | Serial | 1329 | |||
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| Author | Shida Beigpour; Joost Van de Weijer |
 
 
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| Title | Object Recoloring Based on Intrinsic Image Estimation | Type | Conference Article | |||
| Year | 2011 | Publication | 13th IEEE International Conference in Computer Vision | Abbreviated Journal | ||
| Volume | Issue | Pages |
327 - 334 | |||
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| 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. | |||||
| Address | Barcelona | |||||
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| ISSN | 1550-5499 | ISBN | 978-1-4577-1101-5 | Medium | ||
| Area | Expedition | Conference | ICCV | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ BeW2011 | Serial | 1781 | |||
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| Author | Javier Vazquez; Maria Vanrell; Robert Benavente |
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| Title | Color names as a constraint for Computer Vision problems | Type | Conference Article | |||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | ||
| Volume | Issue | Pages |
324–328 | |||
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| Abstract | Computer Vision Problems are usually ill-posed. Constraining de gamut of possible solutions is then a necessary step. Many constrains for different problems have been developed during years. In this paper, we present a different way of constraining some of these problems: the use of color names. In particular, we will focus on segmentation, representation ans constancy. | |||||
| Address | Gjovik (Norway) | |||||
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| Area | Expedition | Conference | CREATE | |||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ VVB2010 | Serial | 1328 | |||
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| Author | Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias |
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| 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 | ||
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| 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. | |||||
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| Notes | CIC; 600.087; 600.140; 600.118 | Approved | no | |||
| Call Number | Admin @ si @ RVL2019 | Serial | 3310 | |||
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| Author | O. Fors; A. Richichi; Xavier Otazu; J. Nuñez |
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| Title | A new wavelet-based approach for the automated treatment of large sets of lunar occultation data | Type | Journal | |||
| Year | 2008 | Publication | Astronomy and Astrohysics | Abbreviated Journal | ||
| Volume | 480 | Issue | Pages |
297–304 | ||
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| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ FRO2008 | Serial | 934 | |||
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| Author | Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus |
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| Title | Color Naming | Type | Book Chapter | |||
| Year | 2012 | Publication | Color in Computer Vision: Fundamentals and Applications | Abbreviated Journal | ||
| Volume | Issue | 17 | Pages |
287-317 | ||
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| Publisher | John Wiley & Sons, Ltd. | Place of Publication | Editor | Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek | ||
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| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ WBV2012 | Serial | 2063 | |||
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| Author | Shida Beigpour; Marc Serra; Joost Van de Weijer; Robert Benavente; Maria Vanrell; Olivier Penacchio; Dimitris Samaras |
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| Title | Intrinsic Image Evaluation On Synthetic Complex Scenes | Type | Conference Article | |||
| Year | 2013 | Publication | 20th IEEE International Conference on Image Processing | Abbreviated Journal | ||
| Volume | Issue | Pages |
285 - 289 | |||
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| Abstract | Scene decomposition into its illuminant, shading, and reflectance intrinsic images is an essential step for scene understanding. Collecting intrinsic image groundtruth data is a laborious task. The assumptions on which the ground-truth
procedures are based limit their application to simple scenes with a single object taken in the absence of indirect lighting and interreflections. We investigate synthetic data for intrinsic image research since the extraction of ground truth is straightforward, and it allows for scenes in more realistic situations (e.g, multiple illuminants and interreflections). With this dataset we aim to motivate researchers to further explore intrinsic image decomposition in complex scenes. |
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| Address | Melbourne; Australia; September 2013 | |||||
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| Area | Expedition | Conference | ICIP | |||
| Notes | CIC; 600.048; 600.052; 600.051 | Approved | no | |||
| Call Number | Admin @ si @ BSW2013 | Serial | 2264 | |||
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| Author | Hassan Ahmed Sial; S. Sancho; Ramon Baldrich; Robert Benavente; Maria Vanrell |
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| Title | Color-based data augmentation for Reflectance Estimation | Type | Conference Article | |||
| Year | 2018 | Publication | 26th Color Imaging Conference | Abbreviated Journal | ||
| Volume | Issue | Pages |
284-289 | |||
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| Abstract | Deep convolutional architectures have shown to be successful frameworks to solve generic computer vision problems. The estimation of intrinsic reflectance from single image is not a solved problem yet. Encoder-Decoder architectures are a perfect approach for pixel-wise reflectance estimation, although it usually suffers from the lack of large datasets. Lack of data can be partially solved with data augmentation, however usual techniques focus on geometric changes which does not help for reflectance estimation. In this paper we propose a color-based data augmentation technique that extends the training data by increasing the variability of chromaticity. Rotation on the red-green blue-yellow plane of an opponent space enable to increase the training set in a coherent and sound way that improves network generalization capability for reflectance estimation. We perform some experiments on the Sintel dataset showing that our color-based augmentation increase performance and overcomes one of the state-of-the-art methods. | |||||
| Address | Vancouver; November 2018 | |||||
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| Area | Expedition | Conference | CIC | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ SSB2018a | Serial | 3129 | |||
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| Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell |
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| Title | Names and Shades of Color for Intrinsic Image Estimation | Type | Conference Article | |||
| Year | 2012 | Publication | 25th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
| Volume | Issue | Pages |
278-285 | |||
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| Abstract | In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance. | |||||
| Address | Providence, Rhode Island | |||||
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| Publisher | IEEE Xplore | Place of Publication | Editor | |||
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| ISSN | 1063-6919 | ISBN | 978-1-4673-1226-4 | Medium | ||
| Area | Expedition | Conference | CVPR | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ SPB2012 | Serial | 2026 | |||
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| Author | Maria Vanrell; Jordi Vitria; Xavier Roca |
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| Title | A multidimensional scaling approach to explore the behavior of a texture perception algorithm. | Type | Journal Article | |||
| Year | 1997 | Publication | Machine Vision and Applications | Abbreviated Journal | ||
| Volume | 9 | Issue | Pages |
262–271 | ||
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| Notes | OR;ISE;CIC;MV | Approved | no | |||
| Call Number | BCNPCL @ bcnpcl @ VVR1997 | Serial | 35 | |||
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| Author | Jaime Moreno; Xavier Otazu; Maria Vanrell |
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| Title | Local Perceptual Weighting in JPEG2000 for Color Images | Type | Conference Article | |||
| Year | 2010 | Publication | 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science | Abbreviated Journal | ||
| Volume | Issue | Pages |
255–260 | |||
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| 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). | |||||
| Address | Joensuu, Finland | |||||
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| ISSN | ISBN | 9781617388897 | Medium | |||
| Area | Expedition | Conference | CGIV/MCS | |||
| Notes | CIC | Approved | no | |||
| Call Number | CAT @ cat @ MOV2010a | Serial | 1307 | |||
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| Author | Bojana Gajic; Eduard Vazquez; Ramon Baldrich |
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| Title | Evaluation of Deep Image Descriptors for Texture Retrieval | Type | Conference Article | |||
| Year | 2017 | Publication | Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) | Abbreviated Journal | ||
| Volume | Issue | Pages |
251-257 | |||
| Keywords | Texture Representation; Texture Retrieval; Convolutional Neural Networks; Psychophysical Evaluation | |||||
| Abstract | The increasing complexity learnt in the layers of a Convolutional Neural Network has proven to be of great help for the task of classification. The topic has received great attention in recently published literature.
Nonetheless, just a handful of works study low-level representations, commonly associated with lower layers. In this paper, we explore recent findings which conclude, counterintuitively, the last layer of the VGG convolutional network is the best to describe a low-level property such as texture. To shed some light on this issue, we are proposing a psychophysical experiment to evaluate the adequacy of different layers of the VGG network for texture retrieval. Results obtained suggest that, whereas the last convolutional layer is a good choice for a specific task of classification, it might not be the best choice as a texture descriptor, showing a very poor performance on texture retrieval. Intermediate layers show the best performance, showing a good combination of basic filters, as in the primary visual cortex, and also a degree of higher level information to describe more complex textures. |
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| Address | Porto, Portugal; 27 February – 1 March 2017 | |||||
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| Area | Expedition | Conference | VISIGRAPP | |||
| Notes | CIC; 600.087 | Approved | no | |||
| Call Number | Admin @ si @ | Serial | 3710 | |||
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| Author | Naila Murray; Eduard Vazquez |
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| Title | Lacuna Restoration: How to choose a neutral colour? | Type | Conference Article | |||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | ||
| Volume | Issue | Pages |
248–252 | |||
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| 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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| Address | Gjovik, Norway | |||||
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| Area | Expedition | Conference | CREATE | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ MuV2010 | Serial | 1297 | |||
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| Author | Partha Pratim Roy; Eduard Vazquez; Josep Llados; Ramon Baldrich; Umapada Pal |
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| Title | A System to Segment Text and Symbols from Color Maps | Type | Book Chapter | |||
| Year | 2008 | Publication | Graphics Recognition. Recent Advances and New Opportunities | Abbreviated Journal | ||
| Volume | 5046 | Issue | Pages |
245-256 | ||
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | |||
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| Notes | DAG;CIC | Approved | no | |||
| Call Number | CAT @ cat @ RVL2008 | Serial | 1005 | |||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke |
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| Title | A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores | Type | Journal Article | |||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR | |
| Volume | 13 | Issue | 4 | Pages |
243-259 | |
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| Abstract | The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers. | |||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | |||
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| ISSN | 1433-2833 | ISBN | Medium | |||
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| Notes | DAG; CAT;CIC | Approved | no | |||
| Call Number | FLS2010b | Serial | 1319 | |||
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| Author | Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez |
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| Title | Adaptation of a computer programming course to the EXHE requirements: evaluation five years later | Type | Miscellaneous | |||
| Year | 2012 | Publication | European Journal of Engineering Education | Abbreviated Journal | ||
| Volume | 37 | Issue | 3 | Pages |
243-254 | |
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| Notes | DAG; CIC; OR; invisible;MV | Approved | no | |||
| Call Number | Admin @ si @ VBL2012 | Serial | 2070 | |||
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| Author | C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger |
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| Title | Limitations of visual gamma corrections in LCD displays | Type | Journal Article | |||
| Year | 2014 | Publication | Displays | Abbreviated Journal | Dis | |
| Volume | 35 | Issue | 5 | Pages |
227–239 | |
| Keywords | Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration | |||||
| Abstract | A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements. | |||||
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| Notes | CIC; DAG; 600.052; 600.077; 600.074 | Approved | no | |||
| Call Number | Admin @ si @ PRK2014 | Serial | 2511 | |||
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| Author | Ivet Rafegas; Maria Vanrell |
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| Title | Color spaces emerging from deep convolutional networks | Type | Conference Article | |||
| Year | 2016 | Publication | 24th Color and Imaging Conference | Abbreviated Journal | ||
| Volume | Issue | Pages |
225-230 | |||
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| Abstract | Award for the best interactive session
Defining color spaces that provide a good encoding of spatio-chromatic properties of color surfaces is an open problem in color science [8, 22]. Related to this, in computer vision the fusion of color with local image features has been studied and evaluated [16]. In human vision research, the cells which are selective to specific color hues along the visual pathway are also a focus of attention [7, 14]. In line with these research aims, in this paper we study how color is encoded in a deep Convolutional Neural Network (CNN) that has been trained on more than one million natural images for object recognition. These convolutional nets achieve impressive performance in computer vision, and rival the representations in human brain. In this paper we explore how color is represented in a CNN architecture that can give some intuition about efficient spatio-chromatic representations. In convolutional layers the activation of a neuron is related to a spatial filter, that combines spatio-chromatic representations. We use an inverted version of it to explore the properties. Using a series of unsupervised methods we classify different type of neurons depending on the color axes they define and we propose an index of color-selectivity of a neuron. We estimate the main color axes that emerge from this trained net and we prove that colorselectivity of neurons decreases from early to deeper layers. |
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| Address | San Diego; USA; November 2016 | |||||
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| Area | Expedition | Conference | CIC | |||
| Notes | CIC | Approved | no | |||
| Call Number | Admin @ si @ RaV2016a | Serial | 2894 | |||
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