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Author Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva
Title 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 Xavier Perez Sala; Cecilio Angulo; Sergio Escalera
Title Biologically Inspired Path Execution Using SURF Flow in Robot Navigation Type Conference Article
Year 2011 Publication 11th International Work Conference on Artificial Neural Networks Abbreviated Journal
Volume II Issue Pages 581--588
Keywords
Abstract An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo.
Address Malaga
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 0302-9743 ISBN 978-3-642-21497-4 Medium
Area Expedition Conference IWANN
Notes HuPBA;MILAB Approved no
Call Number Admin @ si @ PAE2011b Serial 1773
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Author Farhan Riaz; Fernando Vilariño; Mario Dinis-Ribeiro; Miguel Coimbraln
Title Identifying Potentially Cancerous Tissues in Chromoendoscopy Images Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 709-716
Keywords Endoscopy, Computer Assisted Diagnosis, Gradient.
Abstract The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Editor J. Vitria, J.M. Sanches, and M. Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21256-7 Medium
Area 800 Expedition Conference IbPRIA
Notes MV;SIAI Approved no
Call Number Admin @ si @ RVD2011; IAM @ iam @ RVD2011 Serial 1726
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Author Nataliya Shapovalova; Wenjuan Gong; Marco Pedersoli; Xavier Roca; Jordi Gonzalez
Title On Importance of Interactions and Context in Human Action Recognition Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 58-66
Keywords
Abstract This paper is focused on the automatic recognition of human events in static images. Popular techniques use knowledge of the human pose for inferring the action, and the most recent approaches tend to combine pose information with either knowledge of the scene or of the objects with which the human interacts. Our approach makes a step forward in this direction by combining the human pose with the scene in which the human is placed, together with the spatial relationships between humans and objects. Based on standard, simple descriptors like HOG and SIFT, recognition performance is enhanced when these three types of knowledge are taken into account. Results obtained in the PASCAL 2010 Action Recognition Dataset demonstrate that our technique reaches state-of-the-art results using simple descriptors and classifiers.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor J. Vitria, J.M. Sanches, and M. Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number Admin @ si @ SGP2011 Serial 1750
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Author David Fernandez; Josep Llados; Alicia Fornes
Title Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 628-635
Keywords
Abstract There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Place of Publication Editor Jordi Vitria; Joao Miguel Raposo; Mario Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number Admin @ si @ FLF2011 Serial 1742
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Author Anjan Dutta; Josep Llados; Umapada Pal
Title A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 620-627
Keywords
Abstract In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number Admin @ si @ DLP2011a Serial 1738
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Author Simone Balocco; Carlo Gatta; Francesco Ciompi; Oriol Pujol; Xavier Carrillo; J. Mauri; Petia Radeva
Title Combining Growcut and Temporal Correlation for IVUS Lumen Segmentation Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 556-563
Keywords
Abstract The assessment of arterial luminal area, performed by IVUS analysis, is a clinical index used to evaluate the degree of coronary artery disease. In this paper we propose a novel approach to automatically segment the vessel lumen, which combines model-based temporal information extracted from successive frames of the sequence, with spatial classification using the Growcut algorithm. The performance of the method is evaluated by an in vivo experiment on 300 IVUS frames. The automatic and manual segmentation performances in general vessel and stent frames are comparable. The average segmentation error in vessel, stent and bifurcation frames are 0.17±0.08 mm, 0.18±0.07 mm and 0.31±0.12 mm respectively.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ BGC2011a Serial 1741
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Author Mario Rojas; David Masip; Jordi Vitria
Title Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 371-378
Keywords
Abstract Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art.
Address Las Palmas de Gran Canaria. Spain
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 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes OR;MV Approved no
Call Number Admin @ si @ RMV2011a Serial 1731
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Author Muhammad Anwer Rao; David Vazquez; Antonio Lopez
Title Opponent Colors for Human Detection Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 363-370
Keywords Pedestrian Detection; Color; Part Based Models
Abstract Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Heidelberg Editor J. Vitria; J.M. Sanches; M. Hernandez
Language English Summary Language English Original Title Opponent Colors for Human Detection
Series Editor Series Title Lecture Notes on Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes ADAS Approved no
Call Number ADAS @ adas @ RVL2011a Serial 1666
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Author Carlo Gatta; Simone Balocco; Victoria Martin Yuste; Ruben Leta; Petia Radeva
Title Non-rigid Multi-modal Registration of Coronary Arteries Using SIFTflow Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 159-166
Keywords
Abstract The fusion of clinically relevant information coming from different image modalities is an important topic in medical imaging. In particular, different cardiac imaging modalities provides complementary information for the physician: Computer Tomography Angiography (CTA) provides reliable pre-operative information on arteries geometry, even in the presence of chronic total occlusions, while X-Ray Angiography (XRA) allows intra-operative high resolution projections of a specific artery. The non-rigid registration of arteries between these two modalities is a difficult task. In this paper we propose the use of SIFTflow, in registering CTA and XRA images. At the best of our knowledge, this paper proposed SIFTflow as a XRay-CTA registration method for the first time in the literature. To highlight the arteries, so to guide the registration process, the well known Vesselness method has been employed. Results confirm that, to the aim of registration, the arteries must be highlighted and background objects removed as much as possible. Moreover, the comparison with the well known Free Form Deformation technique, suggests that SIFTflow has a great potential in the registration of multi-modal medical images.
Address Las Palmas de Gran Canaria. Spain
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Berlin Editor Jordi Vitria; Joao Miguel Sanches; Mario Hernandez
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes MILAB Approved no
Call Number Admin @ si @ GBM2011 Serial 1752
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 134-143   
Keywords Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.
Abstract This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.
Address Las Palmas de Gran Canaria, June 2011
Corporate Author SpringerLink Thesis
Publisher Place of Publication Editor Vitrià, Jordi and Sanches, João and Hernández, Mario
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 978-3-642-21256-7 Medium
Area 800 Expedition Conference IbPRIA
Notes MV;SIAI Approved no
Call Number IAM @ iam @ BSV2011c Serial 1696
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Author Marina Alberti; Carlo Gatta; Simone Balocco; Francesco Ciompi; Oriol Pujol; Joana Silva; Xavier Carrillo; Petia Radeva
Title Automatic Branching Detection in IVUS Sequences Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 126-133
Keywords
Abstract Atherosclerosis is a vascular pathology affecting the arterial walls, generally located in specific vessel sites, such as bifurcations. In this paper, for the first time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identifies the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classifier to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classifiers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 0302-9743 ISBN 978-3-642-21256-7 Medium
Area Expedition Conference IbPRIA
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ AGB2011 Serial 1740
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Author Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados
Title Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval Type Conference Article
Year 2011 Publication 33rd European Conference on Information Retrieval Abbreviated Journal
Volume 6611 Issue Pages 314-325
Keywords
Abstract In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.
Address Dublin, Ireland
Corporate Author Thesis
Publisher Springer Place of Publication Berlin Editor P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-20160-8 Medium
Area Expedition Conference ECIR
Notes DAG; RV;ADAS Approved no
Call Number Admin @ si @ RAK2011 Serial 1737
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Author Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin
Title Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes Type Book Chapter
Year 2011 Publication Innovations in Intelligent Image Analysis Abbreviated Journal
Volume 339 Issue Pages 7-29
Keywords
Abstract A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Berlin Editor H. Kawasnicka; L.Jain
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1860-949X ISBN 978-3-642-17933-4 Medium
Area Expedition Conference
Notes MILAB;HuPBA Approved no
Call Number Admin @ si @ ETP2011 Serial 1746
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Author Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard
Title A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume 6388 Issue Pages 93–98
Keywords
Abstract We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.
Address
Corporate Author Thesis
Publisher Springer, 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 978-3-642-17710-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ LLR2010 Serial 1459
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