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Author Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
Title A Performance Characterization Algorithm for Symbol Localization Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 260–271
Keywords (up)
Abstract In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
Address
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 978-3-642-13727-3 Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number Admin @ si @ DRV2010 Serial 2406
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Author Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados
Title Symbol Recognition Using a Concept Lattice of Graphical Patterns Type Book Chapter
Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal
Volume 6020 Issue Pages 187-198
Keywords (up)
Abstract In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
Address
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 978-3-642-13727-3 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ RBO2010 Serial 2407
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Author Mirko Arnold; Anarta Ghosh; Stephen Ameling; G Lacey
Title Automatic segmentation and inpainting of specular highlights for endoscopic imaging Type Journal Article
Year 2010 Publication EURASIP Journal on Image and Video Processing Abbreviated Journal EURASIP JIVP
Volume 2010 Issue 9 Pages
Keywords (up)
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 800 Expedition Conference
Notes MV Approved no
Call Number fernando @ fernando @ Serial 2423
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Author Fadi Dornaika; Bogdan Raducanu
Title Single Snapshot 3D Head Pose Initialization for Tracking in Human Robot Interaction Scenario Type Conference Article
Year 2010 Publication 1st International Workshop on Computer Vision for Human-Robot Interaction Abbreviated Journal
Volume Issue Pages 32–39
Keywords (up) 1st International Workshop on Computer Vision for Human-Robot Interaction, in conjunction with IEEE CVPR 2010
Abstract This paper presents an automatic 3D head pose initialization scheme for a real-time face tracker with application to human-robot interaction. It has two main contributions. First, we propose an automatic 3D head pose and person specific face shape estimation, based on a 3D deformable model. The proposed approach serves to initialize our realtime 3D face tracker. What makes this contribution very attractive is that the initialization step can cope with faces
under arbitrary pose, so it is not limited only to near-frontal views. Second, the previous framework is used to develop an application in which the orientation of an AIBO’s camera can be controlled through the imitation of user’s head pose.
In our scenario, this application is used to build panoramic images from overlapping snapshots. Experiments on real videos confirm the robustness and usefulness of the proposed methods.
Address San Francisco; CA; USA; June 2010
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 2160-7508 ISBN 978-1-4244-7029-7 Medium
Area Expedition Conference CVPRW
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ DoR2010a Serial 1309
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Author David Geronimo; Antonio Lopez; Angel Sappa; Thorsten Graf
Title Survey on Pedestrian Detection for Advanced Driver Assistance Systems Type Journal Article
Year 2010 Publication IEEE Transaction on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI
Volume 32 Issue 7 Pages 1239–1258
Keywords (up) ADAS, pedestrian detection, on-board vision, survey
Abstract Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one-after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges.
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 0162-8828 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ GLS2010 Serial 1340
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Author Robert Benavente; C. Alejandro Parraga; Maria Vanrell
Title La influencia del contexto en la definicion de las fronteras entre las categorias cromaticas Type Conference Article
Year 2010 Publication 9th Congreso Nacional del Color Abbreviated Journal
Volume Issue Pages 92–95
Keywords (up) Categorización del color; Apariencia del color; Influencia del contexto; Patrones de Mondrian; Modelos paramétricos
Abstract En este artículo presentamos los resultados de un experimento de categorización de color en el que las muestras se presentaron sobre un fondo multicolor (Mondrian) para simular los efectos del contexto. Los resultados se comparan con los de un experimento previo que, utilizando un paradigma diferente, determinó las fronteras sin tener en cuenta el contexto. El análisis de los resultados muestra que las fronteras obtenidas con el experimento en contexto presentan menos confusión que las obtenidas en el experimento sin contexto.
Address Alicante (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 978-84-9717-144-1 Medium
Area Expedition Conference CNC
Notes CIC Approved no
Call Number CAT @ cat @ BPV2010 Serial 1327
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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 (up) 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 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 Marçal Rusiñol; Agnes Borras; Josep Llados
Title Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images Type Journal Article
Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume 31 Issue 3 Pages 188–201
Keywords (up) Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings
Abstract This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.
Address
Corporate Author Thesis
Publisher Elsevier 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 @ RBL2010 Serial 1177
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Author Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera
Title Deteccion automatica de la dominancia en conversaciones diadicas Type Journal Article
Year 2010 Publication Escritos de Psicologia Abbreviated Journal EP
Volume 3 Issue 2 Pages 41–45
Keywords (up) Dominance detection; Non-verbal communication; Visual features
Abstract Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers' opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences.
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 1989-3809 ISBN Medium
Area Expedition Conference
Notes HUPBA; OR; MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ EMV2010 Serial 1315
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Author Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera
Title Compact Evolutive Design of Error-Correcting Output Codes Type Conference Article
Year 2010 Publication Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Abbreviated Journal
Volume Issue Pages 119-128
Keywords (up) Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization
Abstract The classi cation of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classi ers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classi ers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classi ers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classi ers. Evolutionary computation is used for tuning the parameters of the classi ers and looking for the best Minimal ECOC code con guration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address Barcelona (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 SUEMA
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BBP2010 Serial 1363
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Author Marçal Rusiñol; Josep Llados
Title Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections Type Book Whole
Year 2010 Publication Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections Abbreviated Journal
Volume Issue Pages
Keywords (up) Focused Retrieval , Graphical Pattern Indexation,Graphics Recognition ,Pattern Recognition , Performance Evaluation , Symbol Description ,Symbol Spotting
Abstract The specific problem of symbol recognition in graphical documents requires additional techniques to those developed for character recognition. The most well-known obstacle is the so-called Sayre paradox: Correct recognition requires good segmentation, yet improvement in segmentation is achieved using information provided by the recognition process. This dilemma can be avoided by techniques that identify sets of regions containing useful information. Such symbol-spotting methods allow the detection of symbols in maps or technical drawings without having to fully segment or fully recognize the entire content.

This unique text/reference provides a complete, integrated and large-scale solution to the challenge of designing a robust symbol-spotting method for collections of graphic-rich documents. The book examines a number of features and descriptors, from basic photometric descriptors commonly used in computer vision techniques to those specific to graphical shapes, presenting a methodology which can be used in a wide variety of applications. Additionally, readers are supplied with an insight into the problem of performance evaluation of spotting methods. Some very basic knowledge of pattern recognition, document image analysis and graphics recognition is assumed.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-84996-208-7 Medium
Area Expedition Conference
Notes DAG Approved no
Call Number DAG @ dag @ RuL2010a Serial 1292
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Author Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados
Title Vers une approche foue of encapsulation de graphes: application a la reconnaissance de symboles Type Conference Article
Year 2010 Publication Colloque International Francophone sur l'Écrit et le Document Abbreviated Journal
Volume Issue Pages 169-184
Keywords (up) Fuzzy interval; Graph embedding; Bayesian network; Symbol recognition
Abstract We present a new methodology for symbol recognition, by employing a structural approach for representing visual associations in symbols and a statistical classifier for recognition. A graphic symbol is vectorized, its topological and geometrical details are encoded by an attributed relational graph and a signature is computed for it. Data adapted fuzzy intervals have been introduced for addressing the sensitivity of structural representations to noise. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set, and is deployed in a supervised learning scenario for recognizing query symbols. Experimental results on pre-segmented 2D linear architectural and electronic symbols from GREC databases are presented.
Address Sousse, Tunisia
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 CIFED
Notes DAG Approved no
Call Number DAG @ dag @ LBR2010a Serial 1293
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Author Maurizio Mencuccini; Jordi Martinez-Vilalta; Josep Piñol; Lasse Loepfe; Mireia Burnat ; Xavier Alvarez; Juan Camacho; Debora Gil
Title A quantitative and statistically robust method for the determination of xylem conduit spatial distribution Type Journal Article
Year 2010 Publication American Journal of Botany Abbreviated Journal AJB
Volume 97 Issue 8 Pages 1247-1259
Keywords (up) Geyer; hydraulic conductivity; point pattern analysis; Ripley; Spatstat; vessel clusters; xylem anatomy; xylem network
Abstract Premise of the study: Because of their limited length, xylem conduits need to connect to each other to maintain water transport from roots to leaves. Conduit spatial distribution in a cross section plays an important role in aiding this connectivity. While indices of conduit spatial distribution already exist, they are not well defined statistically. * Methods: We used point pattern analysis to derive new spatial indices. One hundred and five cross-sectional images from different species were transformed into binary images. The resulting point patterns, based on the locations of the conduit centers-of-area, were analyzed to determine whether they departed from randomness. Conduit distribution was then modeled using a spatially explicit stochastic model. * Key results: The presence of conduit randomness, uniformity, or aggregation depended on the spatial scale of the analysis. The large majority of the images showed patterns significantly different from randomness at least at one spatial scale. A strong phylogenetic signal was detected in the spatial variables. * Conclusions: Conduit spatial arrangement has been largely conserved during evolution, especially at small spatial scales. Species in which conduits were aggregated in clusters had a lower conduit density compared to those with uniform distribution. Statistically sound spatial indices must be employed as an aid in the characterization of distributional patterns across species and in models of xylem water transport. Point pattern analysis is a very useful tool in identifying spatial patterns.
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 IAM; Approved no
Call Number IAM @ iam @ MMG2010 Serial 1623
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Author Miquel Ferrer; Ernest Valveny; F. Serratosa; K. Riesen; Horst Bunke
Title Generalized Median Graph Computation by Means of Graph Embedding in Vector Spaces Type Journal Article
Year 2010 Publication Pattern Recognition Abbreviated Journal PR
Volume 43 Issue 4 Pages 1642–1655
Keywords (up) Graph matching; Weighted mean of graphs; Median graph; Graph embedding; Vector spaces
Abstract The median graph has been presented as a useful tool to represent a set of graphs. Nevertheless its computation is very complex and the existing algorithms are restricted to use limited amount of data. In this paper we propose a new approach for the computation of the median graph based on graph embedding. Graphs are embedded into a vector space and the median is computed in the vector domain. We have designed a procedure based on the weighted mean of a pair of graphs to go from the vector domain back to the graph domain in order to obtain a final approximation of the median graph. Experiments on three different databases containing large graphs show that we succeed to compute good approximations of the median graph. We have also applied the median graph to perform some basic classification tasks achieving reasonable good results. These experiments on real data open the door to the application of the median graph to a number of more complex machine learning algorithms where a representative of a set of graphs is needed.
Address
Corporate Author Thesis
Publisher Elsevier 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 @ FVS2010 Serial 1294
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Author Oriol Ramos Terrades; Alejandro Hector Toselli; Nicolas Serrano; Veronica Romero; Enrique Vidal; Alfons Juan
Title Interactive layout analysis and transcription systems for historic handwritten documents Type Conference Article
Year 2010 Publication 10th ACM Symposium on Document Engineering Abbreviated Journal
Volume Issue Pages 219–222
Keywords (up) Handwriting recognition; Interactive predictive processing; Partial supervision; Interactive layout analysis
Abstract The amount of digitized legacy documents has been rising dramatically over the last years due mainly to the increasing number of on-line digital libraries publishing this kind of documents, waiting to be classified and finally transcribed into a textual electronic format (such as ASCII or PDF). Nevertheless, most of the available fully-automatic applications addressing this task are far from being perfect and heavy and inefficient human intervention is often required to check and correct the results of such systems. In contrast, multimodal interactive-predictive approaches may allow the users to participate in the process helping the system to improve the overall performance. With this in mind, two sets of recent advances are introduced in this work: a novel interactive method for text block detection and two multimodal interactive handwritten text transcription systems which use active learning and interactive-predictive technologies in the recognition process.
Address Manchester, United Kingdom
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 ACM
Notes DAG Approved no
Call Number Admin @ si @RTS2010 Serial 1857
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