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Author Anjan Dutta; Josep Llados; Umapada Pal edit  doi
isbn  openurl
  Title Symbol Spotting in Line Drawings Through Graph Paths Hashing Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 982-986  
  Keywords  
  Abstract In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can be efficiently represented by graphs, which ease the accurate localization of the model symbol. Graph paths are the factorized substructures of graphs which enable robust recognition even in the presence of noise and distortion. In our framework, the entire database of the graphical documents is indexed in hash tables by the locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. The spotting method is formulated by a spatial voting scheme to the list of locations of the paths that are decided during the hash table lookup process. We perform detailed experiments with various dataset of line drawings and the results demonstrate the effectiveness and efficiency of the technique.  
  Address Beijing, China  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN 978-1-4577-1350-7 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ DLP2011b Serial 1791  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny edit  url
doi  isbn
openurl 
  Title Wall Patch-Based Segmentation in Architectural Floorplans Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1270-1274  
  Keywords  
  Abstract Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates.  
  Address Beiging, China  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN 978-0-7695-4520-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ HMS2011a Serial 1792  
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Author Dimosthenis Karatzas; Sergi Robles; Joan Mas; Farshad Nourbakhsh; Partha Pratim Roy edit  doi
isbn  openurl
  Title ICDAR 2011 Robust Reading Competition – Challege 1: Reading Text in Born-Digital Images (Web and Email) Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1485-1490  
  Keywords  
  Abstract This paper presents the results of the first Challenge of ICDAR 2011 Robust Reading Competition. Challenge 1 is focused on the extraction of text from born-digital images, specifically from images found in Web pages and emails. The challenge was organized in terms of three tasks that look at different stages of the process: text localization, text segmentation and word recognition. In this paper we present the results of the challenge for all three tasks, and make an open call for continuous participation outside the context of ICDAR 2011.  
  Address Beijing, China  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN 978-1-4577-1350-7 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ KRM2011 Serial 1793  
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Author Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados edit  doi
isbn  openurl
  Title The ICDAR 2011 Music Scores Competition: Staff Removal and Writer Identification Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1511-1515  
  Keywords  
  Abstract In the last years, there has been a growing interest in the analysis of handwritten music scores. In this sense, our goal has been to foster the interest in the analysis of handwritten music scores by the proposal of two different competitions: Staff removal and Writer Identification. Both competitions have been tested on the CVC-MUSCIMA database: a ground-truth of handwritten music score images. This paper describes the competition details, including the dataset and ground-truth, the evaluation metrics, and a short description of the participants, their methods, and the obtained results.  
  Address Beijing, China  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-0-7695-4520-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ FDG2011b Serial 1794  
Permanent link to this record
 

 
Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
openurl 
  Title Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.
 
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher (up) 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 GREC  
  Notes DAG; 600.045; 600.056; 600.061; 601.152 Approved no  
  Call Number Admin @ si @ BDJ2013 Serial 2360  
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Author Sergio Escalera edit   pdf
url  openurl
  Title Multi-Modal Human Behaviour Analysis from Visual Data Sources Type Journal
  Year 2013 Publication ERCIM News journal Abbreviated Journal ERCIM  
  Volume 95 Issue Pages 21-22  
  Keywords  
  Abstract The Human Pose Recovery and Behaviour Analysis group (HuPBA), University of Barcelona, is developing a line of research on multi-modal analysis of humans in visual data. The novel technology is being applied in several scenarios with high social impact, including sign language recognition, assisted technology and supported diagnosis for the elderly and people with mental/physical disabilities, fitness conditioning, and Human Computer Interaction.  
  Address  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0926-4981 ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ Esc2013 Serial 2361  
Permanent link to this record
 

 
Author Xavier Carrillo; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; Petia Radeva; Neus Salvatella; Oriol Pujol; J. Mauri; A. Bayes edit  openurl
  Title Changes in Radial Artery Volume Assessed Using Intravascular Ultrasound: A Comparison of Two Vasodilator Regimens in Transradial Coronary Intervention Type Journal Article
  Year 2011 Publication Journal of Invasive Cardiology Abbreviated Journal JOIC  
  Volume 23 Issue 10 Pages 401-404  
  Keywords radial; vasodilator treatment; percutaneous coronary intervention; IVUS; volumetric IVUS analysis  
  Abstract OBJECTIVES:
This study used intravascular ultrasound (IVUS) to evaluate radial artery volume changes after intraarterial administration of nitroglycerin and/or verapamil.
BACKGROUND:
Radial artery spasm, which is associated with radial artery size, is the main limitation of the transradial approach in percutaneous coronary interventions (PCI).
METHODS:
This prospective, randomized study compared the effect of two intra-arterial vasodilator regimens on radial artery volume: 0.2 mg of nitroglycerin plus 2.5 mg of verapamil (Group 1; n = 15) versus 2.5 mg of verapamil alone (Group 2; n = 15). Radial artery lumen volume was assessed using IVUS at two time points: at baseline (5 minutes after sheath insertion) and post-vasodilator (1 minute after drug administration). The luminal volume of the radial artery was computed using ECOC Random Fields (ECOC-RF), a technique used for automatic segmentation of luminal borders in longitudinal cut images from IVUS sequences.
RESULTS:
There was a significant increase in arterial lumen volume in both groups, with an increase from 451 ± 177 mm³ to 508 ± 192 mm³ (p = 0.001) in Group 1 and from 456 ± 188 mm³ to 509 ± 170 mm³ (p = 0.001) in Group 2. There were no significant differences between the groups in terms of absolute volume increase (58 mm³ versus 53 mm³, respectively; p = 0.65) or in relative volume increase (14% versus 20%, respectively; p = 0.69).
CONCLUSIONS:
Administration of nitroglycerin plus verapamil or verapamil alone to the radial artery resulted in similar increases in arterial lumen volume according to ECOC-RF IVUS measurements.
 
  Address  
  Corporate Author Thesis  
  Publisher (up) 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 MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CFC2011 Serial 1797  
Permanent link to this record
 

 
Author Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne edit  openurl
  Title Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans Type Conference Article
  Year 2011 Publication In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Toronto, Canada  
  Corporate Author Thesis  
  Publisher (up) 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 PIA  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPL2011 Serial 1798  
Permanent link to this record
 

 
Author Simone Balocco; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva edit  doi
isbn  openurl
  Title Plaque Type, Plaque Burden and Wall Shear Stress Relation in Coronary Arteries Assessed by X-ray Angiography and Intravascular Ultrasound: a Qualitative Study Type Conference Article
  Year 2011 Publication 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this paper, we present a complete framework that automatically provides fluid-dynamic and plaque analysis from IVUS and Angiographic sequences. Such framework is used to analyze, in three coronary arteries, the relation between wall shear stress with type and amount of plaque. Preliminary qualitative results show an inverse relation between the wall shear stress and the plaque burden, which is confirmed by the fact that the plaque growth is higher on the wall having concave curvature. Regarding the plaque type it was observed that regions having low shear stress are predominantly fibro-lipidic while the heavy calcifications are in general located in areas of the vessel having high WSS.  
  Address  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-0913-4 Medium  
  Area Expedition Conference ISABEL  
  Notes MILAB Approved no  
  Call Number Admin @ si @ BGC2011b Serial 1799  
Permanent link to this record
 

 
Author E. Serradell; Adriana Romero; R. Leta; Carlo Gatta; Francesc Moreno-Noguer edit  url
openurl 
  Title Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-Ray Images Type Conference Article
  Year 2011 Publication 13th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 850-857  
  Keywords  
  Abstract  
  Address Barcelona  
  Corporate Author Thesis  
  Publisher (up) 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 ICCV  
  Notes MILAB Approved no  
  Call Number Admin @ si @ SRL2011 Serial 1803  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
doi  openurl
  Title Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1078-1082  
  Keywords  
  Abstract This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets.  
  Address Washington; USA; August 2013  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.045; 600.056; 600.061; 601.152 Approved no  
  Call Number Admin @ si @ DLB2013a Serial 2358  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
openurl 
  Title A Product graph based method for dual subgraph matching applied to symbol spotting Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Product graph has been shown to be an efficient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph.
The dual graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix finds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.
 
  Address Bethlehem; PA; USA; August 2013  
  Corporate Author Thesis  
  Publisher (up) 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 GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ DLB2013b Serial 2359  
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca edit   pdf
doi  openurl
  Title Human Action Recognition Using an Ensemble of Body-Part Detectors Type Journal Article
  Year 2013 Publication Expert Systems Abbreviated Journal EXSY  
  Volume 30 Issue 2 Pages 101-114  
  Keywords Human action recognition;body-part detection;hidden Markov model  
  Abstract This paper describes an approach to human action recognition based on a probabilistic optimization model of body parts using hidden Markov model (HMM). Our method is able to distinguish between similar actions by only considering the body parts having major contribution to the actions, for example, legs for walking, jogging and running; arms for boxing, waving and clapping. We apply HMMs to model the stochastic movement of the body parts for action recognition. The HMM construction uses an ensemble of body-part detectors, followed by grouping of part detections, to perform human identification. Three example-based body-part detectors are trained to detect three components of the human body: the head, legs and arms. These detectors cope with viewpoint changes and self-occlusions through the use of ten sub-classifiers that detect body parts over a specific range of viewpoints. Each sub-classifier is a support vector machine trained on features selected for the discriminative power for each particular part/viewpoint combination. Grouping of these detections is performed using a simple geometric constraint model that yields a viewpoint-invariant human detector. We test our approach on three publicly available action datasets: the KTH dataset, Weizmann dataset and HumanEva dataset. Our results illustrate that with a simple and compact representation we can achieve robust recognition of human actions comparable to the most complex, state-of-the-art methods.  
  Address  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ CBG2013 Serial 1809  
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  Title A Selective Spatio-Temporal Interest Point Detector for Human Action Recognition in Complex Scenes Type Conference Article
  Year 2011 Publication 13th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 1776-1783  
  Keywords  
  Abstract Recent progress in the field of human action recognition points towards the use of Spatio-Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this paper we present a new approach for STIP detection by applying surround suppression combined with local and temporal constraints. Our method is significantly different from existing STIP detectors and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-visual words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on existing benchmark datasets, and more challenging datasets of complex scenes, validate our approach and show state-of-the-art performance.  
  Address Barcelona  
  Corporate Author Thesis  
  Publisher (up) Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN 978-1-4577-1101-5 Medium  
  Area Expedition Conference ICCV  
  Notes ISE Approved no  
  Call Number Admin @ si @ CHM2011 Serial 1811  
Permanent link to this record
 

 
Author Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez edit  openurl
  Title Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation Type Conference Article
  Year 2011 Publication 1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address London, United Kingdom  
  Corporate Author Thesis  
  Publisher (up) 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 PERHAPS  
  Notes ISE Approved no  
  Call Number Admin @ si @ GBA2011 Serial 1812  
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