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Author Marçal Rusiñol; Josep Llados; Gemma Sanchez
Title Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings Type Journal Article
Year 2010 Publication Pattern Analysis and Applications Abbreviated Journal PAA
Volume 13 Issue 3 Pages 321-331
Keywords
Abstract In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1433-7541 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ RLS2010 Serial 1165
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Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Traffic sign recognition system with β -correction Type Journal Article
Year 2010 Publication Machine Vision and Applications Abbreviated Journal MVA
Volume 21 Issue 2 Pages 99–111
Keywords
Abstract Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0932-8092 ISBN Medium
Area Expedition Conference
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ EPR2010a Serial 1276
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas
Title Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 3 Pages 229–241
Keywords
Abstract One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.
Address
Corporate Author Thesis
Publisher (down) 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; IF 2009: 1,213 Approved no
Call Number DAG @ dag @ FLS2010a Serial 1288
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Author Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas
Title Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 3 Pages 187-207
Keywords
Abstract This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.
Address
Corporate Author Thesis
Publisher (down) 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 Approved no
Call Number DAG @ dag @ DVP2010 Serial 1289
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke
Title A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores Type Journal Article
Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR
Volume 13 Issue 4 Pages 243-259
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 (down) 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 Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva
Title Classification of Coronary Damage in Chronic Chagasic Patients Type Book Chapter
Year 2010 Publication Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence Abbreviated Journal
Volume 299 Issue Pages 461-478
Keywords Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
Abstract Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor V. Sgurev, M. Hadjiski (eds)
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;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ EPL2010 Serial 1452
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title Symbol recognition: current advances and perspectives Type Book Chapter
Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS
Volume 2390 Issue Pages 104-128
Keywords
Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
Address London, UK
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 3-540-44066-6 Medium
Area Expedition Conference GREC
Notes DAG; IAM; Approved no
Call Number IAM @ iam @ LVS2002 Serial 1572
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Author Pierluigi Casale; Oriol Pujol; Petia Radeva
Title Personalization and User Verification in Wearable Systems using Biometric Walking Patterns Type Journal Article
Year 2012 Publication Personal and Ubiquitous Computing Abbreviated Journal PUC
Volume 16 Issue 5 Pages 563-580
Keywords
Abstract In this article, a novel technique for user’s authentication and verification using gait as a biometric unobtrusive pattern is proposed. The method is based on a two stages pipeline. First, a general activity recognition classifier is personalized for an specific user using a small sample of her/his walking pattern. As a result, the system is much more selective with respect to the new walking pattern. A second stage verifies whether the user is an authorized one or not. This stage is defined as a one-class classification problem. In order to solve this problem, a four-layer architecture is built around the geometric concept of convex hull. This architecture allows to improve robustness to outliers, modeling non-convex shapes, and to take into account temporal coherence information. Two different scenarios are proposed as validation with two different wearable systems. First, a custom high-performance wearable system is built and used in a free environment. A second dataset is acquired from an Android-based commercial device in a ‘wild’ scenario with rough terrains, adversarial conditions, crowded places and obstacles. Results on both systems and datasets are very promising, reducing the verification error rates by an order of magnitude with respect to the state-of-the-art technologies.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1617-4909 ISBN Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ CPR2012 Serial 1706
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Author Jordi Vitria; Joao Sanchez; Miguel Raposo; Mario Hernandez
Title Pattern Recognition and Image Analysis Type Book Whole
Year 2011 Publication 5th Iberian Conference Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages
Keywords
Abstract
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Berlin Editor J. Vitrià; J. Sanchez; M. Raposo; M. Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-2125 Medium
Area Expedition Conference IbPRIA
Notes OR;MV Approved no
Call Number Admin @ si @ VSR2011 Serial 1730
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Author Jon Almazan; Ernest Valveny; Alicia Fornes
Title Deforming the Blurred Shape Model for Shape Description and Recognition Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 1-8
Keywords
Abstract This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Berlin Editor Jordi Vitria; Joao Miguel Raposo; Mario Hernandez
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 DAG; Approved no
Call Number Admin @ si @ AVF2011 Serial 1732
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Author Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich
Title Perception Based Representations for Computational Colour Type Conference Article
Year 2011 Publication 3rd International Workshop on Computational Color Imaging Abbreviated Journal
Volume 6626 Issue Pages 16-30
Keywords colour perception, induction, naming, psychophysical data, saliency, segmentation
Abstract The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.
Address Milan, Italy
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor Raimondo Schettini, Shoji Tominaga, Alain Trémeau
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-20403-6 Medium
Area Expedition Conference CCIW
Notes CIC Approved no
Call Number Admin @ si @ VMB2011 Serial 1733
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Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate
Title 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 (down) 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 Eloi Puertas; Sergio Escalera; Oriol Pujol
Title Generalized Multi-scale Stacked Sequential Learning for Multi-class Classification Type Journal Article
Year 2015 Publication Pattern Analysis and Applications Abbreviated Journal PAA
Volume 18 Issue 2 Pages 247-261
Keywords Stacked sequential learning; Multi-scale; Error-correct output codes (ECOC); Contextual classification
Abstract In many classification problems, neighbor data labels have inherent sequential relationships. Sequential learning algorithms take benefit of these relationships in order to improve generalization. In this paper, we revise the multi-scale sequential learning approach (MSSL) for applying it in the multi-class case (MMSSL). We introduce the error-correcting output codesframework in the MSSL classifiers and propose a formulation for calculating confidence maps from the margins of the base classifiers. In addition, we propose a MMSSL compression approach which reduces the number of features in the extended data set without a loss in performance. The proposed methods are tested on several databases, showing significant performance improvement compared to classical approaches.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1433-7541 ISBN Medium
Area Expedition Conference
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ PEP2013 Serial 2251
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Author Bogdan Raducanu; Fadi Dornaika
Title Texture-independent recognition of facial expressions in image snapshots and videos Type Journal Article
Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA
Volume 24 Issue 4 Pages 811-820
Keywords
Abstract This paper addresses the static and dynamic recognition of basic facial expressions. It has two main contributions. First, we introduce a view- and texture-independent scheme that exploits facial action parameters estimated by an appearance-based 3D face tracker. We represent the learned facial actions associated with different facial expressions by time series. Second, we compare this dynamic scheme with a static one based on analyzing individual snapshots and show that the former performs better than the latter. We provide evaluations of performance using three subspace learning techniques: linear discriminant analysis, non-parametric discriminant analysis and support vector machines.
Address
Corporate Author Thesis
Publisher (down) Springer-Verlag Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0932-8092 ISBN Medium
Area Expedition Conference
Notes OR; 600.046; 605.203;MV Approved no
Call Number Admin @ si @ RaD2013 Serial 2230
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Author Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes
Title On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space Type Conference Article
Year 2012 Publication Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop Abbreviated Journal
Volume 7626 Issue Pages 135-143
Keywords
Abstract Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected.
Address
Corporate Author Thesis
Publisher (down) Springer-Berlag, Berlin Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-34165-6 Medium
Area Expedition Conference SSPR&SPR
Notes DAG Approved no
Call Number Admin @ si @ GVB2012c Serial 2167
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