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Author Jaime Moreno; Xavier Otazu; Maria Vanrell edit  openurl
Title (up) Contribution of CIWaM in JPEG2000 Quantization for Color Images Type Conference Article
Year 2010 Publication Proceedings of The CREATE 2010 Conference Abbreviated Journal  
Volume Issue Pages 132–136  
Keywords  
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(ChromaticInductionWaveletModel).  
Address Gjovik (Norway)  
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 CREATE  
Notes CIC Approved no  
Call Number CAT @ cat @ MOV2010b Serial 1308  
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Author Bojana Gajic; Ramon Baldrich edit  doi
openurl 
Title (up) Cross-domain fashion image retrieval Type Conference Article
Year 2018 Publication CVPR 2018 Workshop on Women in Computer Vision (WiCV 2018, 4th Edition) Abbreviated Journal  
Volume Issue Pages 19500-19502  
Keywords  
Abstract Cross domain image retrieval is a challenging task that implies matching images from one domain to their pairs from another domain. In this paper we focus on fashion image retrieval, which involves matching an image of a fashion item taken by users, to the images of the same item taken in controlled condition, usually by professional photographer. When facing this problem, we have different products
in train and test time, and we use triplet loss to train the network. We stress the importance of proper training of simple architecture, as well as adapting general models to the specific task.		  
Address Salt Lake City, USA; 22 June 2018  
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 CVPRW  
Notes CIC; 600.087 Approved no  
Call Number Admin @ si @ Serial 3709  
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Author Robert Benavente; Laura Igual; Fernando Vilariño edit  isbn
openurl 
Title (up) Current Challenges in Computer Vision Type Book Whole
Year 2008 Publication Proccedings of the Third Internal Workshop Abbreviated Journal  
Volume Issue Pages  
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 978-84-936529-0-6 Medium  
Area Expedition Conference CVCRD  
Notes MILAB;CIC;SIAI Approved no  
Call Number BCNPCL @ bcnpcl @ BIV2008 Serial 1110  
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Author Aleksandr Setkov; Fabio Martinez Carillo; Michele Gouiffes; Christian Jacquemin; Maria Vanrell; Ramon Baldrich edit  doi
isbn  openurl
Title (up) DAcImPro: A Novel Database of Acquired Image Projections and Its Application to Object Recognition Type Conference Article
Year 2015 Publication Advances in Visual Computing. Proceedings of 11th International Symposium, ISVC 2015 Part II Abbreviated Journal  
Volume 9475 Issue Pages 463-473  
Keywords Projector-camera systems; Feature descriptors; Object recognition  
Abstract Projector-camera systems are designed to improve the projection quality by comparing original images with their captured projections, which is usually complicated due to high photometric and geometric variations. Many research works address this problem using their own test data which makes it extremely difficult to compare different proposals. This paper has two main contributions. Firstly, we introduce a new database of acquired image projections (DAcImPro) that, covering photometric and geometric conditions and providing data for ground-truth computation, can serve to evaluate different algorithms in projector-camera systems. Secondly, a new object recognition scenario from acquired projections is presented, which could be of a great interest in such domains, as home video projections and public presentations. We show that the task is more challenging than the classical recognition problem and thus requires additional pre-processing, such as color compensation or projection area selection.  
Address  
Corporate Author Thesis  
Publisher Springer International Publishing Place of Publication Editor  
Language Summary Language Original Title  
Series Editor Series Title Abbreviated Series Title LNCS  
Series Volume Series Issue Edition  
ISSN 0302-9743 ISBN 978-3-319-27862-9 Medium  
Area Expedition Conference ISVC  
Notes CIC Approved no  
Call Number Admin @ si @ SMG2015 Serial 2736  
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Author Robert Benavente edit  openurl
Title (up) Dealing with colour variability: application to a colour naming task Type Report
Year 1999 Publication CVC Technical Report #32 Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address CVC (UAB)  
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 @ Ben1999 Serial 53  
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Author Hassan Ahmed Sial; Ramon Baldrich; Maria Vanrell edit   pdf
url  openurl
Title (up) Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects Type Journal Article
Year 2020 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
Volume 37 Issue 1 Pages 1-15  
Keywords  
Abstract Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues. On the other hand, end-to-end deep learning architectures start to achieve interesting results that we believe could be improved if important physical hints were not ignored. In this work, we present a twofold framework: (a) a flexible generation of images overcoming some classical dataset problems such as larger size jointly with coherent lighting appearance; and (b) a flexible architecture tying physical properties through intrinsic losses. Our proposal is versatile, presents low computation time, and achieves state-of-the-art 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 ISBN Medium  
Area Expedition Conference  
Notes CIC; 600.140; 600.12; 600.118 Approved no  
Call Number Admin @ si @ SBV2019 Serial 3311  
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Author Eduard Vazquez; Ramon Baldrich; Joost Van de Weijer; Maria Vanrell edit   pdf
url  doi
openurl 
Title (up) Describing Reflectances for Colour Segmentation Robust to Shadows, Highlights and Textures Type Journal Article
Year 2011 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
Volume 33 Issue 5 Pages 917-930  
Keywords  
Abstract The segmentation of a single material reflectance is a challenging problem due to the considerable variation in image measurements caused by the geometry of the object, shadows, and specularities. The combination of these effects has been modeled by the dichromatic reflection model. However, the application of the model to real-world images is limited due to unknown acquisition parameters and compression artifacts. In this paper, we present a robust model for the shape of a single material reflectance in histogram space. The method is based on a multilocal creaseness analysis of the histogram which results in a set of ridges representing the material reflectances. The segmentation method derived from these ridges is robust to both shadow, shading and specularities, and texture in real-world images. We further complete the method by incorporating prior knowledge from image statistics, and incorporate spatial coherence by using multiscale color contrast information. Results obtained show that our method clearly outperforms state-of-the-art segmentation methods on a widely used segmentation benchmark, having as a main characteristic its excellent performance in the presence of shadows and highlights at low computational cost.  
Address Los Alamitos; CA; USA;  
Corporate Author Thesis  
Publisher IEEE Computer Society Place of Publication Editor  
Language Summary Language Original Title  
Series Editor Series Title Abbreviated Series Title  
Series Volume Series Issue Edition  
ISSN 0162-8828 ISBN Medium  
Area Expedition Conference  
Notes CIC Approved no  
Call Number Admin @ si @ VBW2011 Serial 1715  
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Author Xavier Otazu; M. Ribo; M. Peracaula; J.M. Paredes; J. Nuñez edit  openurl
Title (up) Detection of superimposed periodic signals using wavelets Type Journal
Year 2002 Publication Monthly Notices of the Royal Astronomical Society, 333, 2: 365–372 (IF: 4.671) Abbreviated Journal  
Volume Issue Pages  
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 @ ORP2002 Serial 272  
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Author Rahat Khan; Joost Van de Weijer; Fahad Shahbaz Khan; Damien Muselet; christophe Ducottet; Cecile Barat edit   pdf
doi  openurl
Title (up) Discriminative Color Descriptors Type Conference Article
Year 2013 Publication IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
Volume Issue Pages 2866 - 2873  
Keywords  
Abstract Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.  
Address Portland; Oregon; June 2013  
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 1063-6919 ISBN Medium  
Area Expedition Conference CVPR  
Notes CIC; 600.048 Approved no  
Call Number Admin @ si @ KWK2013a Serial 2262  
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Author Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez edit   pdf
url  doi
openurl 
Title (up) Discriminative Compact Pyramids for Object and Scene Recognition Type Journal Article
Year 2012 Publication Pattern Recognition Abbreviated Journal PR  
Volume 45 Issue 4 Pages 1627-1636  
Keywords  
Abstract Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets.  
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 ISE; CAT;CIC Approved no  
Call Number Admin @ si @ EKW2012 Serial 1807  
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Author C. Alejandro Parraga; Jordi Roca; Maria Vanrell edit  url
doi  openurl
Title (up) Do Basic Colors Influence Chromatic Adaptation? Type Journal Article
Year 2011 Publication Journal of Vision Abbreviated Journal VSS  
Volume 11 Issue 11 Pages 85  
Keywords  
Abstract Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered.  
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 1534-7362 ISBN Medium  
Area Expedition Conference  
Notes CIC Approved no  
Call Number Admin @ si @ PRV2011 Serial 1759  
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Author Eduard Vazquez; Maria Vanrell edit  openurl
Title (up) Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial Type Miscellaneous
Year 2008 Publication V Jornades d’Innovacio Docent (UAB) Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address Bellaterra (Spain)  
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 @ VaV2008 Serial 1011  
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Author Ricardo Toledo; Ramon Baldrich; Ernest Valveny; Petia Radeva edit  openurl
Title (up) Enhancing snakes for vessel detection in angiography images. Type Miscellaneous
Year 2002 Publication Proceedings of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 139–144. Abbreviated Journal  
Volume Issue Pages  
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 MILAB;DAG;CIC;ADAS Approved no  
Call Number BCNPCL @ bcnpcl @ TBV2002 Serial 300  
Permanent link to this record
 
 
Author Ivet Rafegas; Javier Vazquez; Robert Benavente; Maria Vanrell; Susana Alvarez edit  url
openurl 
Title (up) Enhancing spatio-chromatic representation with more-than-three color coding for image description Type Journal Article
Year 2017 Publication Journal of the Optical Society of America A Abbreviated Journal JOSA A  
Volume 34 Issue 5 Pages 827-837  
Keywords  
Abstract Extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose a new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to enhance the fact that the number of channels is adapted to the image content. The higher color complexity an image has, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding using these color pivots as a basis. To evaluate the proposed approach we measure its efficiency in an image categorization task. We show how a generic descriptor improves its performance at the description level when applied on the MTT coding.  
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 Approved no  
Call Number Admin @ si @ RVB2017 Serial 2892  
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Author Marc Serra edit  openurl
Title (up) Estimating Intrinsic Images from Physical and Categorical Color Cues Type Report
Year 2010 Publication CVC Technical Report Abbreviated Journal  
Volume 151 Issue Pages  
Keywords  
Abstract  
Address  
Corporate Author Thesis Master's 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 @ Ser2010 Serial 1345  
Permanent link to this record
 
 
Author Hassan Ahmed Sial edit  isbn
openurl 
Title (up) Estimating Light Effects from a Single Image: Deep Architectures and Ground-Truth Generation Type Book Whole
Year 2021 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract In this thesis, we explore how to estimate the effects of the light interacting with the scene objects from a single image. To achieve this goal, we focus on recovering intrinsic components like reflectance, shading, or light properties such as color and position using deep architectures. The success of these approaches relies on training on large and diversified image datasets. Therefore, we present several contributions on this such as: (a) a data-augmentation technique; (b) a ground-truth for an existing multi-illuminant dataset; (c) a family of synthetic datasets, SID for Surreal Intrinsic Datasets, with diversified backgrounds and coherent light conditions; and (d) a practical pipeline to create hybrid ground-truths to overcome the complexity of acquiring realistic light conditions in a massive way. In parallel with the creation of datasets, we trained different flexible encoder-decoder deep architectures incorporating physical constraints from the image formation models.

In the last part of the thesis, we apply all the previous experience to two different problems. Firstly, we create a large hybrid Doc3DShade dataset with real shading and synthetic reflectance under complex illumination conditions, that is used to train a two-stage architecture that improves the character recognition task in complex lighting conditions of unwrapped documents. Secondly, we tackle the problem of single image scene relighting by extending both, the SID dataset to present stronger shading and shadows effects, and the deep architectures to use intrinsic components to estimate new relit images.		  
Address September 2021  
Corporate Author Thesis Ph.D. thesis  
Publisher IMPRIMA Place of Publication Editor Maria Vanrell;Ramon Baldrich  
Language Summary Language Original Title  
Series Editor Series Title Abbreviated Series Title  
Series Volume Series Issue Edition  
ISSN ISBN 978-84-122714-8-5 Medium  
Area Expedition Conference  
Notes CIC; Approved no  
Call Number Admin @ si @ Sia2021 Serial 3607  
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Author Robert Benavente; Maria Vanrell; Ramon Baldrich edit  openurl
Title (up) Estimation of Fuzzy Sets for Computational Colour Categorization Type Journal
Year 2004 Publication Color Research and Application, 29(5):342–353 (IF: 0.739) Abbreviated Journal  
Volume Issue Pages  
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 @ BVB2004 Serial 484  
Permanent link to this record
 
 
Author Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg edit   pdf
doi  isbn
openurl 
Title (up) Evaluating the impact of color on texture recognition Type Conference Article
Year 2013 Publication 15th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
Volume 8047 Issue Pages 154-162  
Keywords Color; Texture; image representation  
Abstract State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.
In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets.		  
Address York; UK; August 2013  
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 0302-9743 ISBN 978-3-642-40260-9 Medium  
Area Expedition Conference CAIP  
Notes CIC; 600.048 Approved no  
Call Number Admin @ si @ KWA2013 Serial 2263  
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