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Author Agnes Borras; Francesc Tous; Josep Llados; Maria Vanrell edit   pdf
openurl 
Title (down) High-Level Clothes Description Based on Color-Texture and Structural Features Type Book Chapter
Year 2003 Publication Lecture Notes in Computer Science Abbreviated Journal  
Volume 2652 Issue Pages 108–116  
Keywords  
Abstract This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images.  
Address Springer-Verlag  
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 DAG;CIC Approved no  
Call Number CAT @ cat @ BTL2003a Serial 368  
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Author Xavier Boix; Josep M. Gonfaus; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez edit   pdf
url  doi
openurl 
Title (down) Harmony Potentials: Fusing Global and Local Scale for Semantic Image Segmentation Type Journal Article
Year 2012 Publication International Journal of Computer Vision Abbreviated Journal IJCV  
Volume 96 Issue 1 Pages 83-102  
Keywords  
Abstract The Hierarchical Conditional Random Field(HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF models of image segmentation do not allow multiple classes to be assigned to a single region, which limits their ability to incorporate contextual information across multiple scales.
At higher scales in the image, this representation yields an oversimpli ed model since multiple classes can be reasonably expected to appear within large regions. This simpli ed model particularly limits the impact of information at higher scales. Since class-label information at these scales is usually more reliable than at lower, noisier scales, neglecting this information is undesirable. To
address these issues, we propose a new consistency potential for image labeling problems, which we call the harmony potential. It can encode any possible combi-
nation of labels, penalizing only unlikely combinations of classes. We also propose an e ective sampling strategy over this expanded label set that renders tractable the underlying optimization problem. Our approach obtains state-of-the-art results on two challenging, standard benchmark datasets for semantic image segmentation: PASCAL VOC 2010, and MSRC-21.
 
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 0920-5691 ISBN Medium  
Area Expedition Conference  
Notes ISE;CIC;ADAS Approved no  
Call Number Admin @ si @ BGW2012 Serial 1718  
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Author Josep M. Gonfaus; Xavier Boix; Joost Van de Weijer; Andrew Bagdanov; Joan Serrat; Jordi Gonzalez edit  url
doi  isbn
openurl 
Title (down) Harmony Potentials for Joint Classification and Segmentation Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
Volume Issue Pages 3280–3287  
Keywords  
Abstract Hierarchical conditional random fields have been successfully applied to object segmentation. One reason is their ability to incorporate contextual information at different scales. However, these models do not allow multiple labels to be assigned to a single node. At higher scales in the image, this yields an oversimplified model, since multiple classes can be reasonable expected to appear within one region. This simplified model especially limits the impact that observations at larger scales may have on the CRF model. Neglecting the information at larger scales is undesirable since class-label estimates based on these scales are more reliable than at smaller, noisier scales. To address this problem, we propose a new potential, called harmony potential, which can encode any possible combination of class labels. We propose an effective sampling strategy that renders tractable the underlying optimization problem. Results show that our approach obtains state-of-the-art results on two challenging datasets: Pascal VOC 2009 and MSRC-21.  
Address San Francisco CA, USA  
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 978-1-4244-6984-0 Medium  
Area Expedition Conference CVPR  
Notes ADAS;CIC;ISE Approved no  
Call Number ADAS @ adas @ GBW2010 Serial 1296  
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Author Jose Carlos Rubio edit  openurl
Title (down) Graph matching based on graphical models with application to vehicle tracking and classification at night Type Report
Year 2009 Publication CVC Technical Report Abbreviated Journal  
Volume 144 Issue Pages  
Keywords  
Abstract  
Address  
Corporate Author Computer Vision Center Thesis Master's thesis  
Publisher Place of Publication Bellaterra, Barcelona 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 @ Rub2009 Serial 2398  
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Author Xavier Roca; Jordi Vitria; Maria Vanrell; Juan J. Villanueva edit  openurl
Title (down) Gaze control in a binocular robot systems Type Miscellaneous
Year 1999 Publication Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address Barcelona  
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 OR;ISE;CIC;MV Approved no  
Call Number BCNPCL @ bcnpcl @ RVV1999b Serial 41  
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Author Robert Benavente; Maria Vanrell edit  openurl
Title (down) Fuzzy Colour Naming Based on Sigmoid Membership Functions. Type Miscellaneous
Year 2004 Publication CGIV 2004 Second European Conference on Colour in Graphics, Imaging and Vision, 135:139 Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address Aachen (Germany)  
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 @ BeV2004 Serial 441  
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Author M. Gonzalez-Audicana; Xavier Otazu; O. Fors; R Garcia; J. Nuñez edit  openurl
Title (down) Fusion of different spatial and spectral resolution images: development, apllication and comparison of new methods based on wavelets. Type Miscellaneous
Year 2002 Publication Proceedings of the 1st. International Symposium Recent Advances in Quantitative Remote Sensing. 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 @ GOF2002 Serial 291  
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Author O. Fors; Xavier Otazu; J. Nuñez edit  openurl
Title (down) Fusion Mediante Wavelets de Imagenes Spot-pan y del Satelite Tailandes TMSAT. Type Miscellaneous
Year 2001 Publication Teledeteccion, Medio Ambiente y Cambio Global, IX Congreso Nacional de Teledeteccion, 546–550. Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address Lleida  
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 @ FON2001 Serial 94  
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Author Joost Van de Weijer; Fahad Shahbaz Khan edit   pdf
doi  isbn
openurl 
Title (down) Fusing Color and Shape for Bag-of-Words Based Object Recognition Type Conference Article
Year 2013 Publication 4th Computational Color Imaging Workshop Abbreviated Journal  
Volume 7786 Issue Pages 25-34  
Keywords Object Recognition; color features; bag-of-words; image classification  
Abstract In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcomings by exploiting top-down information in the bag-of-words pipeline: color attention which is motivated from human vision, and Portmanteau vocabularies which are based on information theoretic compression of product vocabularies. We point out several remaining challenges in cue fusion and provide directions for future research.  
Address Chiba; Japan; March 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 978-3-642-36699-4 Medium  
Area Expedition Conference CCIW  
Notes CIC; 600.048 Approved no  
Call Number Admin @ si @ WeK2013 Serial 2283  
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Author Fernando Lopez; J.M. Valiente; Ramon Baldrich; Maria Vanrell edit  doi
openurl 
Title (down) Fast surface grading using color statistics in the CIELab space Type Conference Article
Year 2005 Publication Pattern Recognition and Image Analysis. IbPRIA 2005 Abbreviated Journal  
Volume LNCS 3523 Issue Pages 66-673  
Keywords  
Abstract  
Address Germany  
Corporate Author Thesis  
Publisher Place of Publication Editor  
Language Summary Language Original Title  
Series Editor LNCS Series Title Abbreviated Series Title  
Series Volume Series Issue Edition  
ISSN ISBN Medium  
Area Expedition Conference IbPRIA  
Notes CIC Approved no  
Call Number CAT @ cat @ LVB2005 Serial 641  
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Author Maria Vanrell edit  openurl
Title (down) Exploring the space of behaviour of a texture perception algorithm Type Report
Year 1997 Publication CVC Technical Report #12 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 @ Van1997 Serial 523  
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Author Ricard Balague edit  openurl
Title (down) Exploring the combination of color cues for intrinsic image decomposition Type Report
Year 2014 Publication CVC Technical Report Abbreviated Journal  
Volume 178 Issue Pages  
Keywords  
Abstract Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth.  
Address UAB; September 2014  
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; 600.074 Approved no  
Call Number Admin @ si @ Bal2014 Serial 2579  
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Author Ivet Rafegas edit  openurl
Title (down) Exploring Low-Level Vision Models. Case Study: Saliency Prediction Type Report
Year 2013 Publication CVC Technical Report Abbreviated Journal  
Volume 175 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 @ Raf2013 Serial 2409  
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Author Francesc Tous; Maria Vanrell; Ramon Baldrich edit  openurl
Title (down) Exploring Colour Constancy Solutions. Type Miscellaneous
Year 2004 Publication CGIV 2004 Second European Conference on Colour in Graphics, Imaging, and Vision, 24:29 Abbreviated Journal  
Volume Issue Pages  
Keywords  
Abstract  
Address Aachen (Germany)  
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 @ TVB2004 Serial 452  
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Author Bojana Gajic; Eduard Vazquez; Ramon Baldrich edit  url
openurl 
Title (down) 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.
 
Address Porto, Portugal; 27 February – 1 March 2017  
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 VISIGRAPP  
Notes CIC; 600.087 Approved no  
Call Number Admin @ si @ Serial 3710  
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Author Fahad Shahbaz Khan; Joost Van de Weijer; Sadiq Ali; Michael Felsberg edit   pdf
doi  isbn
openurl 
Title (down) 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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Author Robert Benavente; Maria Vanrell; Ramon Baldrich edit  openurl
Title (down) 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  
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Author Hassan Ahmed Sial edit  isbn
openurl 
Title (down) 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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