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Author Joan Mas; Gemma Sanchez; Josep Llados
Title SSP: Sketching slide Presentations, a Syntactic Approach Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages
Keywords
Abstract (up) The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide.
Address La Rochelle; France; July 2009
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 GREC
Notes DAG Approved no
Call Number DAG @ dag @ MSL2009a Serial 1441
Permanent link to this record
 
 
Author Albert Andaluz
Title LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction Type Report
Year 2009 Publication CVC Technical Report Abbreviated Journal
Volume 142 Issue Pages
Keywords Active Contour Models; Snakes; Active Shape Models; Deformable Templates; Left Ventricle Segmentation; Generalized Orthogonal Procrustes Analysis; Harmonic Phase Flow; Principal Component Analysis; Tagged Magnetic Resonance
Abstract (up) The Diagnosis of Left Ventricle (LV) pathologies is related to regional wall motion analysis. Health indicator scores such as the rotation and the torsion are useful for the diagnose of the Left Ventricle (LV) function. However, this requires proper identification of LV segments. On one hand, manual segmentation is robust, but it is slow and requires medical expertise. On the other hand, the tag pattern in Tagged Magnetic Resonance (TMR) sequences is a problem for the automatic segmentation of the LV boundaries. Consequently, we propose a method based in the classical formulation of parametric Snakes, combined with Active Shape models. Our semantic definition of the LV is tagged tissue that experiences motion in the systolic cycle. This defines two energy potentials for the Snake convergence. Additionally, the mean shape corrects excessive deviation from the anatomical shape. We have validated our approach in 15 healthy volunteers and two short axis cuts. In this way, we have compared the automatic segmentations to manual shapes outlined by medical experts. Also, we have explored the accuracy of clinical scores computed using automatic contours. The results show minor divergence in the approximation and the manual segmentations as well as robust computation of clinical scores in all cases. From this we conclude that the proposed method is a promising support tool for clinical analysis.
Address
Corporate Author Thesis Master's thesis
Publisher Place of Publication Bellaterra 08193, Barcelona, Spain 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 @ And2009 Serial 1667
Permanent link to this record
 
 
Author Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich
Title Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset Type Journal Article
Year 2009 Publication Journal of Imaging Science and Technology Abbreviated Journal
Volume 53 Issue 3 Pages 031105–9
Keywords
Abstract (up) The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene.
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 CIC Approved no
Call Number CAT @ cat @ VPV2009a Serial 1171
Permanent link to this record
 
 
Author Antonio Clavelli; Dimosthenis Karatzas
Title Text Segmentation in Colour Posters from the Spanish Civil War Era Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 181 - 185
Keywords
Abstract (up) The extraction of textual content from colour documents of a graphical nature is a complicated task. The text can be rendered in any colour, size and orientation while the existence of complex background graphics with repetitive patterns can make its localization and segmentation extremely difficult.
Here, we propose a new method for extracting textual content from such colour images that makes no assumption as to the size of the characters, their orientation or colour, while it is tolerant to characters that do not follow a straight baseline. We evaluate this method on a collection of documents with historical
connotations: the Posters from the Spanish Civil War.
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 1520-5363 ISBN 978-1-4244-4500-4 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number DAG @ dag @ ClK2009 Serial 1172
Permanent link to this record
 
 
Author David Rotger
Title Analysis and Multi-Modal Fusion of coronary Images Type Book Whole
Year 2009 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract (up) The framework of this thesis is to study in detail different techniques and tools for medical image registration in order to ease the daily life of clinical experts in cardiology. The first aim of this thesis is providing computer tools for
fusing IVUS and angiogram data is of high clinical interest to help the physicians locate in IVUS data and decide which lesion is observed, how long it is, how far from a bifurcation or another lesions stays, etc. This thesis proves and
validates that we can segment the catheter path in angiographies using geodesic snakes (based on fast marching algorithm), a three-dimensional reconstruction of the catheter inspired in stereo vision and a new technique to fuse IVUS
and angiograms that establishes exact correspondences between them. We have developed a new workstation called iFusion that has four strong advantages: registration of IVUS and angiographic images with sub-pixel precision, it works on- and off-line, it is independent on the X-ray system and there is no need of daily calibration. The second aim of the thesis is devoted to developing a computer-aided analysis of IVUS for image-guided intervention. We have designed, implemented
and validated a robust algorithm for stent extraction and reconstruction from IVUS videos. We consider a very special and recent kind of stents, bioabsorbable stents that represent a great clinical challenge due to their property to be
absorbed by time and thus avoiding the “danger” of neostenosis as one of the main problems of metallic stents. We present a new and very promising algorithm based on an optimized cascade of multiple classifiers to automatically detect individual stent struts of a very novel bioabsorbable drug eluting coronary stent. This problem represents a very challenging target given the variability in contrast, shape and grey levels of the regions to be detected, what is
denoted by the high variability between the specialists (inter-observer variability of 0.14~$\pm$0.12). The obtained results of the automatic strut detection are within the inter-observer variability.
Address Barcelona (Espanya)
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Petia Radeva
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number Admin @ si @ Rot2009 Serial 1261
Permanent link to this record
 
 
Author Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva
Title Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification Type Journal Article
Year 2009 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS
Volume 10 Issue 1 Pages 113–126
Keywords
Abstract (up) The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.
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 1524-9050 ISBN Medium
Area Expedition Conference
Notes OR;MILAB;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ BEV2008 Serial 1116
Permanent link to this record
 
 
Author Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva
Title ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences Type Conference Article
Year 2009 Publication 12th International Conference on Medical Image and Computer Assisted Intervention Abbreviated Journal
Volume 5762 Issue II Pages
Keywords
Abstract (up) The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers.
Address London, UK
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 978-3-642-04270-6 Medium
Area Expedition Conference MICCAI
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPF2009 Serial 1228
Permanent link to this record
 
 
Author Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke
Title A Recursive Embedding Approach to Median Graph Computation Type Conference Article
Year 2009 Publication 7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition Abbreviated Journal
Volume 5534 Issue Pages 113–123
Keywords
Abstract (up) The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches.
Address Venice, Italy
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 978-3-642-02123-7 Medium
Area Expedition Conference GBR
Notes DAG Approved no
Call Number DAG @ dag @ FKV2009 Serial 1173
Permanent link to this record
 
 
Author Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez
Title Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach Type Journal Article
Year 2009 Publication International Journal of Electronic Commerce Abbreviated Journal
Volume 14 Issue 1 Pages 89-108
Keywords
Abstract (up) The paper presents a factorization-based approach to make predictions in recommender systems. These systems are widely used in electronic commerce to help customers find products according to their preferences. Taking into account the customer's ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the system. The proposed factorization-based approach uses all the information provided to compute the predicted ratings, in the same way as approaches based on Singular Value Decomposition (SVD). The main advantage of this technique versus SVD-based approaches is that it can deal with missing data. It also has a smaller computational cost. Experimental results with public data sets are provided to show that the proposed adapted factorization approach gives better predicted ratings than a widely used SVD-based approach.
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 1086-4415 ISBN Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number ADAS @ adas @ JSL2009b Serial 1237
Permanent link to this record
 
 
Author Ricard Coll; Alicia Fornes; Josep Llados
Title Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment Type Conference Article
Year 2009 Publication 10th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1081–1085
Keywords
Abstract (up) The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach.
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 1520-5363 ISBN 978-1-4244-4500-4 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number DAG @ dag @ CFL2009 Serial 1221
Permanent link to this record
 
 
Author Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez
Title A Riemmanian approach to cardiac fiber architecture modelling Type Conference Article
Year 2009 Publication 1st International Conference on Mathematical & Computational Biomedical Engineering Abbreviated Journal
Volume Issue Pages 59-62
Keywords cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.
Abstract (up) There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts.
Address
Corporate Author Thesis
Publisher Place of Publication Swansea (UK) Editor Nithiarasu, R.L.R.V.L.
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CMBE
Notes IAM Approved no
Call Number IAM @ iam @ FGA2009 Serial 1520
Permanent link to this record
 
 
Author Oriol Pujol; David Masip
Title Geometry-Based Ensembles: Toward a Structural Characterization of the Classification Boundary Type Journal Article
Year 2009 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI
Volume 31 Issue 6 Pages 1140–1146
Keywords
Abstract (up) This article introduces a novel binary discriminative learning technique based on the approximation of the non-linear decision boundary by a piece-wise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points – points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and non-linear behavior is obtained. The simplicity of the method allows its extension to cope with some of nowadays machine learning challenges, such as online learning, large scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database. Finally, we apply our technique in online and large scale scenarios, and in six real life computer vision and pattern recognition problems: gender recognition, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease severity detection, clef classification and action recognition using a 3D accelerometer data. The results are promising and this paper opens a line of research that deserves further attention
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 OR;HuPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ PuM2009 Serial 1252
Permanent link to this record
 
 
Author D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez
Title Characterizing conversational group dynamics using nonverbal behaviour Type Conference Article
Year 2009 Publication 10th IEEE International Conference on Multimedia and Expo Abbreviated Journal
Volume Issue Pages 370–373
Keywords
Abstract (up) This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%.
Address New York, USA
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 1945-7871 ISBN 978-1-4244-4290-4 Medium
Area Expedition Conference ICME
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ JRG2009 Serial 1217
Permanent link to this record
 
 
Author Bogdan Raducanu; Jordi Vitria; D. Gatica-Perez
Title You are Fired! Nonverbal Role Analysis in Competitive Meetings Type Conference Article
Year 2009 Publication IEEE International Conference on Audio, Speech and Signal Processing Abbreviated Journal
Volume Issue Pages 1949–1952
Keywords
Abstract (up) This paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. For our study, we made use of ldquoThe Apprenticerdquo reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. The current study was carried out using nonverbal audio cues. Results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words.
Address Taipei, Taiwan
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 1520-6149 ISBN 978-1-4244-2353-8 Medium
Area Expedition Conference ICASSP
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ RVG2009 Serial 1154
Permanent link to this record
 
 
Author Daniel Ponsa; Antonio Lopez
Title Variance reduction techniques in particle-based visual contour Tracking Type Journal Article
Year 2009 Publication Pattern Recognition Abbreviated Journal PR
Volume 42 Issue 11 Pages 2372–2391
Keywords Contour tracking; Active shape models; Kalman filter; Particle filter; Importance sampling; Unscented particle filter; Rao-Blackwellization; Partitioned sampling
Abstract (up) This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done.
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 ADAS Approved no
Call Number ADAS @ adas @ PoL2009a Serial 1168
Permanent link to this record