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Author Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard
Title Fuzzy Multilevel Graph Embedding Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 2 Pages 551-565
Keywords Pattern recognition; Graphics recognition; Graph clustering; Graph classification; Explicit graph embedding; Fuzzy logic
Abstract Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding bridges the gap between structural and statistical pattern recognition. We extract the topological, structural and attribute information from a graph and encode numeric details by fuzzy histograms and symbolic details by crisp histograms. The histograms are concatenated to achieve a simple and straightforward embedding of graph into a low-dimensional numeric feature vector. Experimentation on standard public graph datasets shows that our method outperforms the state-of-the-art methods of graph embedding for richly attributed graphs.
Address
Corporate Author Thesis (up)
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203 Approved no
Call Number Admin @ si @ LRL2013a Serial 2270
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Author Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez
Title Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance Type Conference Article
Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal
Volume 1 Issue Pages 153--161
Keywords Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model
Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability
Address Barcelona; February 2013
Corporate Author Thesis (up)
Publisher SciTePress Place of Publication Portugal Editor Sebastiano Battiato and José Braz
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-989-8565-47-1 Medium
Area 800 Expedition Conference VISAPP
Notes IAM;MV; 600.044; 600.047; 600.060; 605.203 Approved no
Call Number IAM @ iam @ SGR2013 Serial 2123
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Author Anjan Dutta; Josep Llados; Umapada Pal
Title A symbol spotting approach in graphical documents by hashing serialized graphs Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 3 Pages 752-768
Keywords Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing
Abstract In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by 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. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique.
Address
Corporate Author Thesis (up)
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203; 601.152 Approved no
Call Number Admin @ si @ DLP2012 Serial 2127
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Author Laura Igual; Agata Lapedriza; Ricard Borras
Title Robust Gait-Based Gender Classification using Depth Cameras Type Journal Article
Year 2013 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ
Volume 37 Issue 1 Pages 72-80
Keywords
Abstract This article presents a new approach for gait-based gender recognition using depth cameras, that can run in real time. The main contribution of this study is a new fast feature extraction strategy that uses the 3D point cloud obtained from the frames in a gait cycle. For each frame, these points are aligned according to their centroid and grouped. After that, they are projected into their PCA plane, obtaining a representation of the cycle particularly robust against view changes. Then, final discriminative features are computed by first making a histogram of the projected points and then using linear discriminant analysis. To test the method we have used the DGait database, which is currently the only publicly available database for gait analysis that includes depth information. We have performed experiments on manually labeled cycles and over whole video sequences, and the results show that our method improves the accuracy significantly, compared with state-of-the-art systems which do not use depth information. Furthermore, our approach is insensitive to illumination changes, given that it discards the RGB information. That makes the method especially suitable for real applications, as illustrated in the last part of the experiments section.
Address
Corporate Author Thesis (up)
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 MILAB; OR;MV Approved no
Call Number Admin @ si @ ILB2013 Serial 2144
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Author Michal Drozdzal; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva
Title Adaptable image cuts for motility inspection using WCE Type Journal Article
Year 2013 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG
Volume 37 Issue 1 Pages 72-80
Keywords
Abstract The Wireless Capsule Endoscopy (WCE) technology allows the visualization of the whole small intestine tract. Since the capsule is freely moving, mainly by the means of peristalsis, the data acquired during the study gives a lot of information about the intestinal motility. However, due to: (1) huge amount of frames, (2) complex intestinal scene appearance and (3) intestinal dynamics that make difficult the visualization of the small intestine physiological phenomena, the analysis of the WCE data requires computer-aided systems to speed up the analysis. In this paper, we propose an efficient algorithm for building a novel representation of the WCE video data, optimal for motility analysis and inspection. The algorithm transforms the 3D video data into 2D longitudinal view by choosing the most informative, from the intestinal motility point of view, part of each frame. This step maximizes the lumen visibility in its longitudinal extension. The task of finding “the best longitudinal view” has been defined as a cost function optimization problem which global minimum is obtained by using Dynamic Programming. Validation on both synthetic data and WCE data shows that the adaptive longitudinal view is a good alternative to the traditional motility analysis done by video analysis. The proposed novel data representation a new, holistic insight into the small intestine motility, allowing to easily define and analyze motility events that are difficult to spot by analyzing WCE video. Moreover, the visual inspection of small intestine motility is 4 times faster then by means of video skimming of the WCE.
Address
Corporate Author Thesis (up)
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 MILAB; OR; 600.046; 605.203 Approved no
Call Number Admin @ si @ DSM2012 Serial 2151
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Author David Geronimo; Joan Serrat; Antonio Lopez; Ramon Baldrich
Title Traffic sign recognition for computer vision project-based learning Type Journal Article
Year 2013 Publication IEEE Transactions on Education Abbreviated Journal T-EDUC
Volume 56 Issue 3 Pages 364-371
Keywords traffic signs
Abstract This paper presents a graduate course project on computer vision. The aim of the project is to detect and recognize traffic signs in video sequences recorded by an on-board vehicle camera. This is a demanding problem, given that traffic sign recognition is one of the most challenging problems for driving assistance systems. Equally, it is motivating for the students given that it is a real-life problem. Furthermore, it gives them the opportunity to appreciate the difficulty of real-world vision problems and to assess the extent to which this problem can be solved by modern computer vision and pattern classification techniques taught in the classroom. The learning objectives of the course are introduced, as are the constraints imposed on its design, such as the diversity of students' background and the amount of time they and their instructors dedicate to the course. The paper also describes the course contents, schedule, and how the project-based learning approach is applied. The outcomes of the course are discussed, including both the students' marks and their personal feedback.
Address
Corporate Author Thesis (up)
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0018-9359 ISBN Medium
Area Expedition Conference
Notes ADAS; CIC Approved no
Call Number Admin @ si @ GSL2013; ADAS @ adas @ Serial 2160
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Author Joan Serrat; Felipe Lumbreras; Antonio Lopez
Title Cost estimation of custom hoses from STL files and CAD drawings Type Journal Article
Year 2013 Publication Computers in Industry Abbreviated Journal COMPUTIND
Volume 64 Issue 3 Pages 299-309
Keywords On-line quotation; STL format; Regression; Gaussian process
Abstract We present a method for the cost estimation of custom hoses from CAD models. They can come in two formats, which are easy to generate: a STL file or the image of a CAD drawing showing several orthogonal projections. The challenges in either cases are, first, to obtain from them a high level 3D description of the shape, and second, to learn a regression function for the prediction of the manufacturing time, based on geometric features of the reconstructed shape. The chosen description is the 3D line along the medial axis of the tube and the diameter of the circular sections along it. In order to extract it from STL files, we have adapted RANSAC, a robust parametric fitting algorithm. As for CAD drawing images, we propose a new technique for 3D reconstruction from data entered on any number of orthogonal projections. The regression function is a Gaussian process, which does not constrain the function to adopt any specific form and is governed by just two parameters. We assess the accuracy of the manufacturing time estimation by k-fold cross validation on 171 STL file models for which the time is provided by an expert. The results show the feasibility of the method, whereby the relative error for 80% of the testing samples is below 15%.
Address
Corporate Author Thesis (up)
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 ADAS; 600.057; 600.054; 605.203 Approved no
Call Number Admin @ si @ SLL2013; ADAS @ adas @ Serial 2161
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Author Fadi Dornaika; Abdelmalik Moujahid; Bogdan Raducanu
Title Facial expression recognition using tracked facial actions: Classifier performance analysis Type Journal Article
Year 2013 Publication Engineering Applications of Artificial Intelligence Abbreviated Journal EAAI
Volume 26 Issue 1 Pages 467-477
Keywords Visual face tracking; 3D deformable models; Facial actions; Dynamic facial expression recognition; Human–computer interaction
Abstract In this paper, we address the analysis and recognition of facial expressions in continuous videos. More precisely, we study classifiers performance that exploit head pose independent temporal facial action parameters. These are provided by an appearance-based 3D face tracker that simultaneously provides the 3D head pose and facial actions. The use of such tracker makes the recognition pose- and texture-independent. Two different schemes are studied. The first scheme adopts a dynamic time warping technique for recognizing expressions where training data are given by temporal signatures associated with different universal facial expressions. The second scheme models temporal signatures associated with facial actions with fixed length feature vectors (observations), and uses some machine learning algorithms in order to recognize the displayed expression. Experiments quantified the performance of different schemes. These were carried out on CMU video sequences and home-made video sequences. The results show that the use of dimension reduction techniques on the extracted time series can improve the classification performance. Moreover, these experiments show that the best recognition rate can be above 90%.
Address
Corporate Author Thesis (up)
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 OR; 600.046;MV Approved no
Call Number Admin @ si @ DMR2013 Serial 2185
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Author David Roche; Debora Gil; Jesus Giraldo
Title Multiple active receptor conformation, agonist efficacy and maximum effect of the system: the conformation-based operational model of agonism, Type Journal Article
Year 2013 Publication Drug Discovery Today Abbreviated Journal DDT
Volume 18 Issue 7-8 Pages 365-371
Keywords
Abstract The operational model of agonism assumes that the maximum effect a particular receptor system can achieve (the Em parameter) is fixed. Em estimates are above but close to the asymptotic maximum effects of endogenous agonists. The concept of Em is contradicted by superagonists and those positive allosteric modulators that significantly increase the maximum effect of endogenous agonists. An extension of the operational model is proposed that assumes that the Em parameter does not necessarily have a single value for a receptor system but has multiple values associated to multiple active receptor conformations. The model provides a mechanistic link between active receptor conformation and agonist efficacy, which can be useful for the analysis of agonist response under different receptor scenarios.
Address
Corporate Author Thesis (up)
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 IAM; 600.057; 600.054 Approved no
Call Number IAM @ iam @ RGG2013a Serial 2190
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Author Mikhail Mozerov
Title Constrained Optical Flow Estimation as a Matching Problem Type Journal Article
Year 2013 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume 22 Issue 5 Pages 2044-2055
Keywords
Abstract In general, discretization in the motion vector domain yields an intractable number of labels. In this paper we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2D disparity labeling map of the desired discrete motion vector function. One of the goals of the proposed paper is estimating coarse distribution of motion vectors and then utilizing this distribution as global constraints for discrete optical flow estimation. This pre-estimation is done with a simple frame-to-frame correlation technique also known as the digital symmetric-phase-only-filter (SPOF). We discover a strong correlation between the output of the SPOF and the motion vector distribution of the related optical flow. The two step matching paradigm for optical flow estimation is applied: pixel accuracy (integer flow), and subpixel accuracy estimation. The matching problem is solved by global optimization. Experiments on the Middlebury optical flow datasets confirm our intuitive assumptions about strong correlation between motion vector distribution of optical flow and maximal peaks of SPOF outputs. The overall performance of the proposed method is promising and achieves state-of-the-art results on the Middlebury benchmark.
Address
Corporate Author Thesis (up)
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1057-7149 ISBN Medium
Area Expedition Conference
Notes ISE Approved no
Call Number Admin @ si @ Moz2013 Serial 2191
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Author Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester
Title Geometric Steerable Medial Maps Type Journal Article
Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA
Volume 24 Issue 6 Pages 1255-1266
Keywords Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction
Abstract In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume.
Address
Corporate Author Thesis (up)
Publisher Springer Berlin Heidelberg Place of Publication Editor Mubarak Shah
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0932-8092 ISBN Medium
Area Expedition Conference
Notes IAM; 605.203; 600.060; 600.044 Approved no
Call Number IAM @ iam @ VGB2013 Serial 2192
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Author Gemma Roig; Xavier Boix; R. de Nijs; Sebastian Ramos; K. Kühnlenz; Luc Van Gool
Title Active MAP Inference in CRFs for Efficient Semantic Segmentation Type Conference Article
Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal
Volume Issue Pages 2312 - 2319
Keywords Semantic Segmentation
Abstract Most MAP inference algorithms for CRFs optimize an energy function knowing all the potentials. In this paper, we focus on CRFs where the computational cost of instantiating the potentials is orders of magnitude higher than MAP inference. This is often the case in semantic image segmentation, where most potentials are instantiated by slow classifiers fed with costly features. We introduce Active MAP inference 1) to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest of the parameters of the potentials unknown, and 2) to estimate the MAP labeling from such incomplete energy function. Results for semantic segmentation benchmarks, namely PASCAL VOC 2010 [5] and MSRC-21 [19], show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains.
Address Sydney; Australia; December 2013
Corporate Author Thesis (up)
Publisher 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 Medium
Area Expedition Conference ICCV
Notes ADAS; 600.057 Approved no
Call Number ADAS @ adas @ RBN2013 Serial 2377
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Author David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo
Title Interactive Training of Human Detectors Type Book Chapter
Year 2013 Publication Multiodal Interaction in Image and Video Applications Abbreviated Journal
Volume 48 Issue Pages 169-182
Keywords Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation
Abstract Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations.
Address Springer Heidelberg New York Dordrecht London
Corporate Author Thesis (up)
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium
Area Expedition Conference
Notes ADAS; 600.057; 600.054; 605.203 Approved no
Call Number VLP2013; ADAS @ adas @ vlp2013 Serial 2193
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Author Ferran Poveda; Debora Gil; Enric Marti; Albert Andaluz; Manel Ballester;Francesc Carreras Costa
Title Helical structure of the cardiac ventricular anatomy assessed by Diffusion Tensor Magnetic Resonance Imaging multi-resolution tractography Type Journal Article
Year 2013 Publication Revista Española de Cardiología Abbreviated Journal REC
Volume 66 Issue 10 Pages 782-790
Keywords Heart;Diffusion magnetic resonance imaging;Diffusion tractography;Helical heart;Myocardial ventricular band.
Abstract Deep understanding of myocardial structure linking morphology and function of the heart would unravel crucial knowledge for medical and surgical clinical procedures and studies. Several conceptual models of myocardial fiber organization have been proposed but the lack of an automatic and objective methodology prevented an agreement. We sought to deepen in this knowledge through advanced computer graphic representations of the myocardial fiber architecture by diffusion tensor magnetic resonance imaging (DT-MRI).
We performed automatic tractography reconstruction of unsegmented DT-MRI canine heart datasets coming from the public database of the Johns Hopkins University. Full scale tractographies have been build with 200 seeds and are composed by streamlines computed on the vectorial field of primary eigenvectors given at the diffusion tensor volumes. Also, we introduced a novel multi-scale visualization technique in order to obtain a simplified tractography. This methodology allowed to keep the main geometric features of the fiber tracts, making easier to decipher the main properties of the architectural organization of the heart.
On the analysis of the output from our tractographic representations we found exact correlation with low-level details of myocardial architecture, but also with the more abstract conceptualization of a continuous helical ventricular myocardial fiber array.
Objective analysis of myocardial architecture by an automated method, including the entire myocardium and using several 3D levels of complexity, reveals a continuous helical myocardial fiber arrangement of both right and left ventricles, supporting the anatomical model of the helical ventricular myocardial band described by Torrent-Guasp.
Address
Corporate Author Thesis (up)
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 IAM; 600.044; 600.060 Approved no
Call Number IAM @ iam @ PGM2013 Serial 2194
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Author David Roche; Debora Gil; Jesus Giraldo
Title Mechanistic analysis of the function of agonists and allosteric modulators: Reconciling two-state and operational models Type Journal Article
Year 2013 Publication British Journal of Pharmacology Abbreviated Journal BJP
Volume 169 Issue 6 Pages 1189-202
Keywords
Abstract Two-state and operational models of both agonism and allosterism are compared to identify and characterize common pharmacological parameters. To account for the receptor-dependent basal response, constitutive receptor activity is considered in the operational models. By arranging two-state models as the fraction of active receptors and operational models as the fractional response relative to the maximum effect of the system, a one-by-one correspondence between parameters is found. The comparative analysis allows a better understanding of complex allosteric interactions. In particular, the inclusion of constitutive receptor activity in the operational model of allosterism allows the characterization of modulators able to lower the basal response of the system; that is, allosteric modulators with negative intrinsic efficacy. Theoretical simulations and overall goodness of fit of the models to simulated data suggest that it is feasible to apply the models to experimental data and constitute one step forward in receptor theory formalism.
Address
Corporate Author Thesis (up)
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; 600.044; 605.203 Approved no
Call Number IAM @ iam @ RGG2013b Serial 2195
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