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Author Miquel Ferrer; Ernest Valveny; F. Serratosa
Title Spectral Median Graphs Applied to Graphical Symbol Recognition Type Book Chapter
Year 2006 Publication (down) 11th Iberoamerican Congress on Pattern Recognition (CIARP´06), J.P. Martinez–Trinidad et al. (Eds.), LNCS 4225: 774–783 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Cancun (Mexico)
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 Approved no
Call Number DAG @ dag @ FVS2006b Serial 698
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Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva
Title Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions Type Book Chapter
Year 2006 Publication (down) 11th Iberoamerican Congress on Pattern Recognition Abbreviated Journal
Volume 4225 Issue Pages 178–187
Keywords
Abstract This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns.
Address Cancun (Mexico)
Corporate Author Thesis
Publisher Springer Verlag Place of Publication Berlin Heidelberg Editor .F. Mart ́ınez-Trinidad et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area 800 Expedition Conference
Notes MV;OR;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f Serial 728
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Author Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Carolina Malagelada; Petia Radeva
Title A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment Type Book Chapter
Year 2006 Publication (down) 11th Iberoamerican Congress on Pattern Recognition Abbreviated Journal
Volume 4225 Issue Pages 188–197
Keywords
Abstract Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.
Address Cancun (Mexico)
Corporate Author Thesis
Publisher Springer Verlag Place of Publication Berlin-Heidelberg Editor J.P. Martinez–Trinidad et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area 800 Expedition Conference CIARP06
Notes MV;OR;MILAB;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e Serial 729
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Author Albert Tatjer; Bhalaji Nagarajan; Ricardo Marques; Petia Radeva
Title CCLM: Class-Conditional Label Noise Modelling Type Conference Article
Year 2023 Publication (down) 11th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 14062 Issue Pages 3-14
Keywords
Abstract The performance of deep neural networks highly depends on the quality and volume of the training data. However, cost-effective labelling processes such as crowdsourcing and web crawling often lead to data with noisy (i.e., wrong) labels. Making models robust to this label noise is thus of prime importance. A common approach is using loss distributions to model the label noise. However, the robustness of these methods highly depends on the accuracy of the division of training set into clean and noisy samples. In this work, we dive in this research direction highlighting the existing problem of treating this distribution globally and propose a class-conditional approach to split the clean and noisy samples. We apply our approach to the popular DivideMix algorithm and show how the local treatment fares better with respect to the global treatment of loss distribution. We validate our hypothesis on two popular benchmark datasets and show substantial improvements over the baseline experiments. We further analyze the effectiveness of the proposal using two different metrics – Noise Division Accuracy and Classiness.
Address Alicante; Spain; June 2023
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference IbPRIA
Notes MILAB Approved no
Call Number Admin @ si @ TNM2023 Serial 3925
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Author Pau Riba; Josep Llados; Alicia Fornes
Title Error-tolerant coarse-to-fine matching model for hierarchical graphs Type Conference Article
Year 2017 Publication (down) 11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition Abbreviated Journal
Volume 10310 Issue Pages 107-117
Keywords Graph matching; Hierarchical graph; Graph-based representation; Coarse-to-fine matching
Abstract Graph-based representations are effective tools to capture structural information from visual elements. However, retrieving a query graph from a large database of graphs implies a high computational complexity. Moreover, these representations are very sensitive to noise or small changes. In this work, a novel hierarchical graph representation is designed. Using graph clustering techniques adapted from graph-based social media analysis, we propose to generate a hierarchy able to deal with different levels of abstraction while keeping information about the topology. For the proposed representations, a coarse-to-fine matching method is defined. These approaches are validated using real scenarios such as classification of colour images and handwritten word spotting.
Address Anacapri; Italy; May 2017
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor Pasquale Foggia; Cheng-Lin Liu; Mario Vento
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GbRPR
Notes DAG; 600.097; 601.302; 600.121 Approved no
Call Number Admin @ si @ RLF2017a Serial 2951
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Author Pau Riba; Alicia Fornes; Josep Llados
Title Towards the Alignment of Handwritten Music Scores Type Conference Article
Year 2015 Publication (down) 11th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract It is very common to find different versions of the same music work in archives of Opera Theaters. These differences correspond to modifications and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study. This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such differences. Given the difficulties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the staff lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results.
Address Nancy; France; August 2015
Corporate Author Thesis
Publisher Springer International Publishing Place of Publication Editor Bart Lamiroy; Rafael Dueire Lins
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-319-52158-9 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ Serial 2874
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Author David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes
Title Sequential Word Spotting in Historical Handwritten Documents Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 101 - 105
Keywords
Abstract In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered
index pages of family names.
Address Tours; Francia; April 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 ISBN 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 600.061; 600.056; 602.006; 600.077 Approved no
Call Number Admin @ si @ FML2014 Serial 2462
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Author Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier
Title Color descriptor for content-based drawing retrieval Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 267 - 271
Keywords
Abstract Human detection in computer vision field is an active field of research. Extending this to human-like drawings such as the main characters in comic book stories is not trivial. Comics analysis is a very recent field of research at the intersection of graphics, texts, objects and people recognition. The detection of the main comic characters is an essential step towards a fully automatic comic book understanding. This paper presents a color-based approach for comics character retrieval using content-based drawing retrieval and color palette.
Address Tours; Francia; April 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 ISBN 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 600.056; 600.077 Approved no
Call Number Admin @ si @ RKB2014 Serial 2479
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Author Dimosthenis Karatzas; Sergi Robles; Lluis Gomez
Title An on-line platform for ground truthing and performance evaluation of text extraction systems Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 242 - 246
Keywords
Abstract This paper presents a set of on-line software tools for creating ground truth and calculating performance evaluation metrics for text extraction tasks such as localization, segmentation and recognition. The platform supports the definition of comprehensive ground truth information at different text representation levels while it offers centralised management and quality control of the ground truthing effort. It implements a range of state of the art performance evaluation algorithms and offers functionality for the definition of evaluation scenarios, on-line calculation of various performance metrics and visualisation of the results. The
presented platform, which comprises the backbone of the ICDAR 2011 (challenge 1) and 2013 (challenges 1 and 2) Robust Reading competitions, is now made available for public use.
Address Tours; Francia; April 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 ISBN 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 600.056; 600.077 Approved no
Call Number Admin @ si @ KRG2014 Serial 2491
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes
Title A Novel Learning-free Word Spotting Approach Based on Graph Representation Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 207-211
Keywords
Abstract Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of 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. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods.
Address Tours; France; April 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 ISBN 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 600.061; 602.006; 600.077 Approved no
Call Number Admin @ si @ WEG2014b Serial 2517
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Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades
Title Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 156-160
Keywords
Abstract This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising.
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 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 600.077 Approved no
Call Number Admin @ si @ DTR2014 Serial 2543
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Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier
Title Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images Type Conference Article
Year 2014 Publication (down) 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal
Volume Issue Pages 181 - 185
Keywords
Abstract Mobile document image acquisition is a new trend raising serious issues in business document processing workflows. Such digitization procedure is unreliable, and integrates many distortions which must be detected as soon as possible, on the mobile, to avoid paying data transmission fees, and losing information due to the inability to re-capture later a document with temporary availability. In this context, out-of-focus blur is major issue: users have no direct control over it, and it seriously degrades OCR recognition. In this paper, we concentrate on the estimation of focus quality, to ensure a sufficient legibility of a document image for OCR processing. We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on document images, which are fast to compute and require no training. Second, we show that a combination of those measures enables state-of-the art performance regarding the correlation with OCR accuracy. The resulting approach is fast, robust, and easy to implement in a mobile device. Experiments are performed on a public dataset, and precise details about image processing are given.
Address Tours; France; April 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 ISBN 978-1-4799-3243-6 Medium
Area Expedition Conference DAS
Notes DAG; 601.223; 600.077 Approved no
Call Number Admin @ si @ RCO2014a Serial 2545
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Author Mireia Sole; Joan Blanco; Debora Gil; Oliver Valero; G. Fonseka; M. Lawrie; Francesca Vidal; Zaida Sarrate
Title Chromosome Territories in Mice Spermatogenesis: A new three-dimensional methodology of study Type Conference Article
Year 2017 Publication (down) 11th European CytoGenesis Conference Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Florencia; Italia; July 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 ECA
Notes IAM; 600.096; 600.145 Approved no
Call Number Admin @ si @ SBG2017a Serial 2936
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Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva
Title Recursive Coarse-to-Fine Localization for fast Object Recognition Type Conference Article
Year 2010 Publication (down) 11th European Conference on Computer Vision Abbreviated Journal
Volume 6313 Issue II Pages 280–293
Keywords
Abstract Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter.
Address Crete (Greece)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 978-3-642-15566-6 Medium
Area Expedition Conference ECCV
Notes ISE Approved no
Call Number DAG @ dag @ PGB2010 Serial 1438
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Author Carles Fernandez; Jordi Gonzalez; Xavier Roca
Title Automatic Learning of Background Semantics in Generic Surveilled Scenes Type Conference Article
Year 2010 Publication (down) 11th European Conference on Computer Vision Abbreviated Journal
Volume 6313 Issue II Pages 678–692
Keywords
Abstract Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis.
Address Crete (Greece)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 978-3-642-15551-2 Medium
Area Expedition Conference ECCV
Notes ISE Approved no
Call Number ISE @ ise @ FGR2010 Serial 1439
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