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Author Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez; Xavier Roca
Title (up) A coarse-to-fine approach for fast deformable object detection Type Journal Article
Year 2015 Publication Pattern Recognition Abbreviated Journal PR
Volume 48 Issue 5 Pages 1844-1853
Keywords
Abstract We present a method that can dramatically accelerate object detection with part based models. The method is based on the observation that the cost of detection is likely to be dominated by the cost of matching each part to the image, and not by the cost of computing the optimal configuration of the parts as commonly assumed. Therefore accelerating detection requires minimizing the number of
part-to-image comparisons. To this end we propose a multiple-resolutions hierarchical part based model and a corresponding coarse-to-fine inference procedure that recursively eliminates from the search space unpromising part
placements. The method yields a ten-fold speedup over the standard dynamic programming approach and is complementary to the cascade-of-parts approach of [9]. Compared to the latter, our method does not have parameters to be determined empirically, which simplifies its use during the training of the model. Most importantly, the two techniques can be combined to obtain a very significant speedup, of two orders of magnitude in some cases. We evaluate our method extensively on the PASCAL VOC and INRIA datasets, demonstrating a very high increase in the detection speed with little degradation of the accuracy.
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 ISE; 600.078; 602.005; 605.001; 302.012 Approved no
Call Number Admin @ si @ PVG2015 Serial 2628
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Author Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
Title (up) A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 453-458
Keywords
Abstract In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
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 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ AFF2012 Serial 1983
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes
Title (up) A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance Type Conference Article
Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3074 - 3079
Keywords word spotting; coarse-to-fine mechamism; graphbased representation; graph embedding; graph edit distance
Abstract Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. Aiming at developing a practical and efficient word spotting approach for large-scale historical handwritten documents, a fast and coarse comparison is first applied to prune the regions that are not similar to the query based on the graph embedding methodology. Afterwards, the query and regions of interest are compared by graph edit distance based on the Dynamic Time Warping alignment. The proposed approach is evaluated on a public dataset containing 50 pages of historical marriage license records. The results show that the proposed approach achieves a compromise between efficiency and accuracy.
Address Stockholm; Sweden; August 2014
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 1051-4651 ISBN Medium
Area Expedition Conference ICPR
Notes DAG; 600.061; 602.006; 600.077 Approved no
Call Number Admin @ si @ WEG2014a Serial 2515
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Author Robert Benavente; Maria Vanrell
Title (up) A colour naming experiment Type Report
Year 2001 Publication CVC Technical Report #56 Abbreviated Journal
Volume Issue Pages
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Abstract
Address CVC (UAB)
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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 @ BeV2001 Serial 78
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Author Javier Vazquez; Maria Vanrell; Anna Salvatella; Eduard Vazquez
Title (up) A colour space based on the image content Type Book Chapter
Year 2007 Publication Artificial Intelligence Research and Development, C. Angulo and L. Godo, pp 205–212 IOS Press Abbreviated Journal
Volume Issue Pages
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Abstract
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes CIC Approved no
Call Number CAT @ cat @ VVS2007 Serial 829
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke
Title (up) 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
Keywords
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.
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 1433-2833 ISBN Medium
Area Expedition Conference
Notes DAG; CAT;CIC Approved no
Call Number FLS2010b Serial 1319
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Author Javier Vazquez; G. D. Finlayson; Maria Vanrell
Title (up) A compact singularity function to predict WCS data and unique hues 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 33–38
Keywords
Abstract Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors.
Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation.

In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure.
Address Joensuu, Finland
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 9781617388897 Medium
Area Expedition Conference CGIV/MCS
Notes CIC Approved no
Call Number CAT @ cat @ VFV2010 Serial 1324
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Author Tadashi Araki; Nobutaka Ikeda; Nilanjan Dey; Sayan Chakraborty; Luca Saba; Dinesh Kumar; Elisa Cuadrado Godia; Xiaoyi Jiang; Ajay Gupta; Petia Radeva; John R. Laird; Andrew Nicolaides; Jasjit S. Suri
Title (up) A comparative approach of four different image registration techniques for quantitative assessment of coronary artery calcium lesions using intravascular ultrasound Type Journal Article
Year 2015 Publication Computer Methods and Programs in Biomedicine Abbreviated Journal CMPB
Volume 118 Issue 2 Pages 158-172
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Abstract
Address
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Area Expedition Conference
Notes MILAB Approved no
Call Number Admin @ si @ AID2015 Serial 2640
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Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier; Josep Llados
Title (up) A Comparative Study of Local Detectors and Descriptors for Mobile Document Classification Type Conference Article
Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal
Volume Issue Pages 596-600
Keywords
Abstract In this paper we conduct a comparative study of local key-point detectors and local descriptors for the specific task of mobile document classification. A classification architecture based on direct matching of local descriptors is used as baseline for the comparative study. A set of four different key-point
detectors and four different local descriptors are tested in all the possible combinations. The experiments are conducted in a database consisting of 30 model documents acquired on 6 different backgrounds, totaling more than 36.000 test images.
Address Nancy; France; August 2015
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 ICDAR
Notes DAG; 600.084; 600.61; 601.223; 600.077 Approved no
Call Number Admin @ si @ RCO2015 Serial 2684
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Author Jordi Gonzalez; J. Varona; Xavier Roca; Juan J. Villanueva
Title (up) A Comparison Framework for Walking Performances using aSpaces Type Journal
Year 2005 Publication Electronic Letters on Computer Vision and Image Analysis, Special Issue on articulated Motion, 5(3):105–116 (Electronic Letters: IF: 1.016) Abbreviated Journal
Volume Issue Pages
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Abstract
Address
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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 ISE Approved no
Call Number ISE @ ise @ GVR2005 Serial 623
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Author David Guillamet; Jordi Vitria
Title (up) A Comparison of Local versus Global Color Histograms for Object Recognition. Type Miscellaneous
Year 2000 Publication 15 th International Conference on Pattern Recognition, 2:422–425. Abbreviated Journal
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Abstract
Address Barcelona.
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Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ GuV2000 b Serial 229
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Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate
Title (up) A Complete Confidence Framework for Optical Flow Type Conference Article
Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal
Volume 7584 Issue 2 Pages 124-133
Keywords Optical flow, confidence measures, sparsification plots, error prediction plots
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Florence, Italy, October 7-13, 2012 Editor Andrea Fusiello, Vittorio Murino ,Rita Cucchiara
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-33867-0 Medium
Area Expedition Conference ECCVW
Notes IAM;ADAS; Approved no
Call Number IAM @ iam @ MGH2012b Serial 1991
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Author Partha Pratim Roy; Josep Llados; Umapada Pal
Title (up) A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information Type Conference Article
Year 2009 Publication 5th International Conference on Computer Vision Theory and Applications Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Lisboa, Portugal
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 978-989-8111-69-2 Medium
Area Expedition Conference VISAPP
Notes DAG Approved no
Call Number DAG @ dag @ RLP2009 Serial 1238
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Author Albin Soutif; Antonio Carta; Andrea Cossu; Julio Hurtado; Hamed Hemati; Vincenzo Lomonaco; Joost Van de Weijer
Title (up) A Comprehensive Empirical Evaluation on Online Continual Learning Type Conference Article
Year 2023 Publication Visual Continual Learning (ICCV-W) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Online continual learning aims to get closer to a live learning experience by learning directly on a stream of data with temporally shifting distribution and by storing a minimum amount of data from that stream. In this empirical evaluation, we evaluate various methods from the literature that tackle online continual learning. More specifically, we focus on the class-incremental setting in the context of image classification, where the learner must learn new classes incrementally from a stream of data. We compare these methods on the Split-CIFAR100 and Split-TinyImagenet benchmarks, and measure their average accuracy, forgetting, stability, and quality of the representations, to evaluate various aspects of the algorithm at the end but also during the whole training period. We find that most methods suffer from stability and underfitting issues. However, the learned representations are comparable to i.i.d. training under the same computational budget. No clear winner emerges from the results and basic experience replay, when properly tuned and implemented, is a very strong baseline. We release our modular and extensible codebase at this https URL based on the avalanche framework to reproduce our results and encourage future research.
Address Paris; France; October 2023
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 ICCVW
Notes LAMP Approved no
Call Number Admin @ si @ SCC2023 Serial 3938
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Author Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio
Title (up) A computational framework for cancer response assessment based on oncological PET-CT scans Type Journal Article
Year 2014 Publication Computers in Biology and Medicine Abbreviated Journal CBM
Volume 55 Issue Pages 92–99
Keywords Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis
Abstract In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks.
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ SED2014 Serial 2606
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