|   | 
Details
   web
Records
Author (down) 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 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
Permanent link to this record
 

 
Author (down) Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados
Title A Content Spotting System For Line Drawing Graphic Document Images Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume 20 Issue Pages 3420–3423
Keywords
Abstract We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents.
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 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ LBR2010b Serial 1460
Permanent link to this record
 

 
Author (down) 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
Permanent link to this record
 

 
Author (down) Monica Piñol
Title Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning Type Report
Year 2010 Publication CVC Technical Report Abbreviated Journal
Volume 162 Issue Pages
Keywords
Abstract
Address Bellaterra (Barcelona)
Corporate Author Computer Vision Center Thesis Master's 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 ADAS Approved no
Call Number Admin @ si @ Piñ2010 Serial 1936
Permanent link to this record
 

 
Author (down) Mohammad Rouhani; Angel Sappa
Title Relaxing the 3L Algorithm for an Accurate Implicit Polynomial Fitting Type Conference Article
Year 2010 Publication 23rd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal
Volume Issue Pages 3066-3072
Keywords
Abstract This paper presents a novel method to increase the accuracy of linear fitting of implicit polynomials. The proposed method is based on the 3L algorithm philosophy. The novelty lies on the relaxation of the additional constraints, already imposed by the 3L algorithm. Hence, the accuracy of the final solution is increased due to the proper adjustment of the expected values in the aforementioned additional constraints. Although iterative, the proposed approach solves the fitting problem within a linear framework, which is independent of the threshold tuning. Experimental results, both in 2D and 3D, showing improvements in the accuracy of the fitting are presented. Comparisons with both state of the art algorithms and a geometric based one (non-linear fitting), which is used as a ground truth, are provided.
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 1063-6919 ISBN 978-1-4244-6984-0 Medium
Area Expedition Conference CVPR
Notes ADAS Approved no
Call Number ADAS @ adas @ RoS2010a Serial 1303
Permanent link to this record
 

 
Author (down) Mohammad Rouhani; Angel Sappa
Title A Fast accurate Implicit Polynomial Fitting Approach Type Conference Article
Year 2010 Publication 17th IEEE International Conference on Image Processing Abbreviated Journal
Volume Issue Pages 1429–1432
Keywords
Abstract This paper presents a novel hybrid approach that combines state of the art fitting algorithms: algebraic-based and geometric-based. It consists of two steps; first, the 3L algorithm is used as an initialization and then, the obtained result, is improved through a geometric approach. The adopted geometric approach is based on a distance estimation that avoids costly search for the real orthogonal distance. Experimental results are presented as well as quantitative comparisons.
Address Hong-Kong
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 1522-4880 ISBN 978-1-4244-7992-4 Medium
Area Expedition Conference ICIP
Notes ADAS Approved no
Call Number ADAS @ adas @ RoS2010b Serial 1359
Permanent link to this record
 

 
Author (down) 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
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
Permanent link to this record
 

 
Author (down) 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 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
Permanent link to this record
 

 
Author (down) Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez
Title Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences Type Journal Article
Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ
Volume Issue Pages
Keywords
Abstract Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.
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 1110-8657 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number ISE @ ise @ MRR2010 Serial 1208
Permanent link to this record
 

 
Author (down) Miguel Reyes; Jordi Vitria; Petia Radeva; Sergio Escalera
Title Real-time Activity Monitoring of Inpatients Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 35–36
Keywords
Abstract In this paper, we present the development of an application capable of monitoring a set of patient vital signs in real time. The application has been designed to support the medical staff of a hospital. Preliminary results show the suitability
of the system to prevent the injury produced by the agitation of the patients.
Address Girona
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 MICCAT
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ RVR2010 Serial 1477
Permanent link to this record
 

 
Author (down) 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 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
Permanent link to this record
 

 
Author (down) Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva
Title Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications Type Conference Article
Year 2010 Publication European Conference on Machine Learning Abbreviated Journal
Volume I Issue Pages 119-128
Keywords
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 Expedition Conference ECML
Notes MILAB; OR;HUPBA;MV Approved no
Call Number Admin @ si @ BEB2010 Serial 1775
Permanent link to this record
 

 
Author (down) Michal Drozdzal; Laura Igual; Petia Radeva; Jordi Vitria; Carolina Malagelada; Fernando Azpiroz
Title Aligning Endoluminal Scene Sequences in Wireless Capsule Endoscopy Type Conference Article
Year 2010 Publication IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis Abbreviated Journal
Volume Issue Pages 117–124
Keywords
Abstract Intestinal motility analysis is an important examination in detection of various intestinal malfunctions. One of the big challenges of automatic motility analysis is how to compare sequence of images and extract dynamic paterns taking into account the high deformability of the intestine wall as well as the capsule motion. From clinical point of view the ability to align endoluminal scene sequences will help to find regions of similar intestinal activity and in this way will provide a valuable information on intestinal motility problems. This work, for first time, addresses the problem of aligning endoluminal sequences taking into account motion and structure of the intestine. To describe motility in the sequence, we propose different descriptors based on the Sift Flow algorithm, namely: (1) Histograms of Sift Flow Directions to describe the flow course, (2) Sift Descriptors to represent image intestine structure and (3) Sift Flow Magnitude to quantify intestine deformation. We show that the merge of all three descriptors provides robust information on sequence description in terms of motility. Moreover, we develop a novel methodology to rank the intestinal sequences based on the expert feedback about relevance of the results. The experimental results show that the selected descriptors are useful in the alignment and similarity description and the proposed method allows the analysis of the WCE.
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 MMBIA
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIR2010 Serial 1316
Permanent link to this record
 

 
Author (down) Michal Drozdzal; Laura Igual; Jordi Vitria; Petia Radeva; Carolina Malagelada; Fernando Azpiroz
Title SIFT flow-based Sequences Alignment Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue Pages 7–8
Keywords
Abstract
Address Girona, 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 MICCAT
Notes OR;MILAB;MV Approved no
Call Number BCNPCL @ bcnpcl @ DIV2010 Serial 1475
Permanent link to this record
 

 
Author (down) 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 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
Permanent link to this record