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Author Josep Llados; J. Lopez-Krahe; Enric Marti edit  openurl
  Title (down) A Hough-based method for hatched pattern detection in maps and diagrams. Type Miscellaneous
  Year 1999 Publication Proceedings of the International Conference on Document Analysis and Recognition. Abbreviated Journal  
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  Address Bangalore-India  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ LlM1999b Serial 1  
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Author Josep Llados; Enric Marti; Jaime Lopez-Krahe edit   pdf
doi  openurl
  Title (down) A Hough-based method for hatched pattern detection in maps and diagrams Type Conference Article
  Year 1999 Publication Proceeding of the Fifth Int. Conf. Document Analysis and Recognition ICDAR ’99 Abbreviated Journal  
  Volume Issue Pages 479-482  
  Keywords  
  Abstract A hatched area is characterized by a set of parallel straight lines placed at regular intervals. In this paper, a Hough-based schema is introduced to recognize hatched areas in technical documents from attributed graph structures representing the document once it has been vectorized. Defining a Hough-based transform from a graph instead of the raster image allows to drastically reduce the processing time and, second, to obtain more reliable results because straight lines have already been detected in the vectorization step. A second advantage of the proposed method is that no assumptions must be made a priori about the slope and frequency of hatching patterns, but they are computed in run time for each hatched area.  
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  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LIM1999b Serial 1580  
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Author Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; Josepa Mauri; Petia Radeva edit  doi
isbn  openurl
  Title (down) A Holistic Approach for the Detection of Media-Adventitia Border in IVUS Type Conference Article
  Year 2011 Publication 14th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 6893 Issue Pages 401-408  
  Keywords  
  Abstract In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm.  
  Address Toronto, Canada  
  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 978-3-642-23625-9 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPG2011 Serial 1739  
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Author Agata Lapedriza; David Masip; Jordi Vitria edit  openurl
  Title (down) A Hierarchical Approach for Multi-task Logistic Regression Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 4478 Issue Pages 258–265  
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  Address Girona (Spain)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor J. Marti et al.  
  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 OR; MV Approved no  
  Call Number BCNPCL @ bcnpcl @ LMV2007a Serial 902  
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Author Cristhian A. Aguilera-Carrasco; Luis Felipe Gonzalez-Böhme; Francisco Valdes; Francisco Javier Quitral Zapata; Bogdan Raducanu edit  doi
openurl 
  Title (down) A Hand-Drawn Language for Human–Robot Collaboration in Wood Stereotomy Type Journal Article
  Year 2023 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 11 Issue Pages 100975 - 100985  
  Keywords  
  Abstract This study introduces a novel, hand-drawn language designed to foster human-robot collaboration in wood stereotomy, central to carpentry and joinery professions. Based on skilled carpenters’ line and symbol etchings on timber, this language signifies the location, geometry of woodworking joints, and timber placement within a framework. A proof-of-concept prototype has been developed, integrating object detectors, keypoint regression, and traditional computer vision techniques to interpret this language and enable an extensive repertoire of actions. Empirical data attests to the language’s efficacy, with the successful identification of a specific set of symbols on various wood species’ sawn surfaces, achieving a mean average precision (mAP) exceeding 90%. Concurrently, the system can accurately pinpoint critical positions that facilitate robotic comprehension of carpenter-indicated woodworking joint geometry. The positioning error, approximately 3 pixels, meets industry standards.  
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  Notes LAMP Approved no  
  Call Number Admin @ si @ AGV2023 Serial 3969  
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Author Josep Llados; Enric Marti edit  openurl
  Title (down) A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems. Type Miscellaneous
  Year 1999 Publication Machine Graphics & Vision, 8(2):195–211. Abbreviated Journal  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ LlM1999a Serial 187  
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Author Josep Llados; Enric Marti edit  openurl
  Title (down) A graph-edit algorithm for hand-drawn graphical document recognition and their automatic introduction into CAD systems Type Journal Article
  Year 1999 Publication Machine Graphics & Vision Abbreviated Journal  
  Volume 8 Issue Pages 195-211  
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  Area Expedition Conference  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LIM1999 Serial 1568  
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Author David Fernandez; Josep Llados; Alicia Fornes edit  doi
openurl 
  Title (down) A graph-based approach for segmenting touching lines in historical handwritten documents Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 17 Issue 3 Pages 293-312  
  Keywords Text line segmentation; Handwritten documents; Document image processing; Historical document analysis  
  Abstract Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FLF2014 Serial 2459  
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Author Gemma Sanchez; Josep Llados edit  openurl
  Title (down) A Graph Grammar to Recognize Textured Symbols. Type Miscellaneous
  Year 2001 Publication Sixth International Conference on Document Analysis and Recognition, ICDAR 2001, 465–469. Abbreviated Journal  
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  Address USA  
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  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ SLl2001 Serial 162  
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Author David Geronimo edit  isbn
openurl 
  Title (down) A Global Approach to Vision-Based Pedestrian Detection for Advanced Driver Assistance Systems Type Book Whole
  Year 2010 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
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  Abstract At the beginning of the 21th century, traffic accidents have become a major problem not only for developed countries but also for emerging ones. As in other scientific areas in which Artificial Intelligence is becoming a key actor, advanced driver assistance systems, and concretely pedestrian protection systems based on Computer Vision, are becoming a strong topic of research aimed at improving the safety of pedestrians. However, the challenge is of considerable complexity due to the varying appearance of humans (e.g., clothes, size, aspect ratio, shape, etc.), the dynamic nature of on-board systems and the unstructured moving environments that urban scenarios represent. In addition, the required performance is demanding both in terms of computational time and detection rates. In this thesis, instead of focusing on improving specific tasks as it is frequent in the literature, we present a global approach to the problem. Such a global overview starts by the proposal of a generic architecture to be used as a framework both to review the literature and to organize the studied techniques along the thesis. We then focus the research on tasks such as foreground segmentation, object classification and refinement following a general viewpoint and exploring aspects that are not usually analyzed. In order to perform the experiments, we also present a novel pedestrian dataset that consists of three subsets, each one addressed to the evaluation of a different specific task in the system. The results presented in this thesis not only end with a proposal of a pedestrian detection system but also go one step beyond by pointing out new insights, formalizing existing and proposed algorithms, introducing new techniques and evaluating their performance, which we hope will provide new foundations for future research in the area.  
  Address Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Antonio Lopez;Krystian Mikolajczyk;Jaume Amores;Dariu M. Gavrila;Oriol Pujol;Felipe Lumbreras  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-936529-5-1 Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ Ger2010 Serial 1279  
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Author Miguel Angel Bautista; Antonio Hernandez; Sergio Escalera; Laura Igual; Oriol Pujol; Josep Moya; Veronica Violant; Maria Teresa Anguera edit   pdf
doi  openurl
  Title (down) A Gesture Recognition System for Detecting Behavioral Patterns of ADHD Type Journal Article
  Year 2016 Publication IEEE Transactions on System, Man and Cybernetics, Part B Abbreviated Journal TSMCB  
  Volume 46 Issue 1 Pages 136-147  
  Keywords Gesture Recognition; ADHD; Gaussian Mixture Models; Convex Hulls; Dynamic Time Warping; Multi-modal RGB-Depth data  
  Abstract We present an application of gesture recognition using an extension of Dynamic Time Warping (DTW) to recognize behavioural patterns of Attention Deficit Hyperactivity Disorder (ADHD). We propose an extension of DTW using one-class classifiers in order to be able to encode the variability of a gesture category, and thus, perform an alignment between a gesture sample and a gesture class. We model the set of gesture samples of a certain gesture category using either GMMs or an approximation of Convex Hulls. Thus, we add a theoretical contribution to classical warping path in DTW by including local modeling of intra-class gesture variability. This methodology is applied in a clinical context, detecting a group of ADHD behavioural patterns defined by experts in psychology/psychiatry, to provide support to clinicians in the diagnose procedure. The proposed methodology is tested on a novel multi-modal dataset (RGB plus Depth) of ADHD children recordings with behavioural patterns. We obtain satisfying results when compared to standard state-of-the-art approaches in the DTW context.  
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  Notes HuPBA; MILAB; Approved no  
  Call Number Admin @ si @ BHE2016 Serial 2566  
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera edit  url
doi  openurl
  Title (down) A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding Type Journal Article
  Year 2013 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 46 Issue 10 Pages 2830-2839  
  Keywords Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification  
  Abstract Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques.  
  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 0031-3203 ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ BGE2013a Serial 2247  
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Author Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados edit   pdf
doi  openurl
  Title (down) A Generic Image Retrieval Method for Date Estimation of Historical Document Collections Type Conference Article
  Year 2022 Publication Document Analysis Systems.15th IAPR International Workshop, (DAS2022) Abbreviated Journal  
  Volume 13237 Issue Pages 583–597  
  Keywords Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG  
  Abstract Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.  
  Address La Rochelle, France; May 22–25, 2022  
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  Area Expedition Conference DAS  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ MGR2022 Serial 3694  
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Author Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke edit  openurl
  Title (down) A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach Type Journal Article
  Year 2011 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 115 Issue 7 Pages 919-928  
  Keywords Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition  
  Abstract The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods.  
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  Notes DAG Approved no  
  Call Number IAM @ iam @ FKV2011 Serial 1831  
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Author Josep Llados; Dimosthenis Karatzas; Joan Mas; Gemma Sanchez edit  openurl
  Title (down) A Generic Architecture for the Conversion of Document Collections into Semantically Annotated Digital Archives Type Journal
  Year 2008 Publication Journal of Universal Computer Science Abbreviated Journal  
  Volume 14 Issue 18 Pages 2912–2935  
  Keywords Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition  
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  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ LKM2008 Serial 1142  
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