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Author A. Sanfeliu; Juan J. Villanueva
Title An approach of visual motion analysis Type Journal Article
Year 2005 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 26 Issue 3 Pages 355–368
Keywords
Abstract IF: 1.138
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Area Expedition Conference
Notes Approved no
Call Number ISE @ ise @ SaV2005 Serial 561
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Author Jaume Amores; Petia Radeva
Title Registration and Retrieval of Highly Elastic Bodies using Contextual Information Type Journal Article
Year 2005 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 26 Issue 11 Pages 1720–1731
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Abstract IF: 1.138
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Publisher Place of Publication Editor
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Notes ADAS;MILAB Approved no
Call Number ADAS @ adas @ AmR2005b Serial 592
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Author Francesco Ciompi; Oriol Pujol; Carlo Gatta; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva
Title Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization Type Journal Article
Year 2010 Publication International Journal of Cardiovascular Imaging Abbreviated Journal IJCI
Volume (up) 26 Issue 7 Pages 763–779
Keywords
Abstract Accurate detection of in-vivo vulnerable plaque in coronary arteries is still an open problem. Recent studies show that it is highly related to tissue structure and composition. Intravascular Ultrasound (IVUS) is a powerful imaging technique that gives a detailed cross-sectional image of the vessel, allowing to explore arteries morphology. IVUS data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue. The main drawback of this method is the few number of available case studies and validated data due to the complex procedure of histological analysis of the tissue. On the other hand, IVUS data from in-vivo cases is easy to obtain but it can not be histologically validated. In this work, we propose to enhance the in-vitro training data set by selectively including examples from in-vivo plaques. For this purpose, a Sequential Floating Forward Selection method is reformulated in the context of plaque characterization. The enhanced classifier performance is validated on in-vitro data set, yielding an overall accuracy of 91.59% in discriminating among fibrotic, lipidic and calcified plaques, while reducing the gap between in-vivo and in-vitro data analysis. Experimental results suggest that the obtained classifier could be properly applied on in-vivo plaque characterization and also demonstrate that the common hypothesis of assuming the difference between in-vivo and in-vitro as negligible is incorrect.
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1569-5794 ISBN Medium
Area Expedition Conference
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPG2010 Serial 1305
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Author Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta
Title On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents Type Journal Article
Year 2012 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI
Volume (up) 26 Issue 5 Pages 1263002-126027
Keywords Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025
Abstract 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images.
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Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ LRF2012 Serial 2128
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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 (up) 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
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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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 Katerine Diaz; Francesc J. Ferri; W. Diaz
Title Incremental Generalized Discriminative Common Vectors for Image Classification Type Journal Article
Year 2015 Publication IEEE Transactions on Neural Networks and Learning Systems Abbreviated Journal TNNLS
Volume (up) 26 Issue 8 Pages 1761 - 1775
Keywords
Abstract Subspace-based methods have become popular due to their ability to appropriately represent complex data in such a way that both dimensionality is reduced and discriminativeness is enhanced. Several recent works have concentrated on the discriminative common vector (DCV) method and other closely related algorithms also based on the concept of null space. In this paper, we present a generalized incremental formulation of the DCV methods, which allows the update of a given model by considering the addition of new examples even from unseen classes. Having efficient incremental formulations of well-behaved batch algorithms allows us to conveniently adapt previously trained classifiers without the need of recomputing them from scratch. The proposed generalized incremental method has been empirically validated in different case studies from different application domains (faces, objects, and handwritten digits) considering several different scenarios in which new data are continuously added at different rates starting from an initial model.
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Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2162-237X ISBN Medium
Area Expedition Conference
Notes ADAS; 600.076 Approved no
Call Number Admin @ si @ DFD2015 Serial 2547
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Author Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title Growing Algorithm for Intersection Detection (GRAID) in branching patterns Type Journal Article
Year 2015 Publication Machine Vision and Applications Abbreviated Journal MVAP
Volume (up) 26 Issue 2 Pages 387-400
Keywords Bifurcation ; Crossroad; Intersection ;Retina ; Vessel
Abstract Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed.
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Notes ;SIAI Approved no
Call Number Admin @ si @MBS2015 Serial 2777
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Author Mikhail Mozerov; Joost Van de Weijer
Title Improved Recursive Geodesic Distance Computation for Edge Preserving Filter Type Journal Article
Year 2017 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume (up) 26 Issue 8 Pages 3696 - 3706
Keywords Geodesic distance filter; color image filtering; image enhancement
Abstract All known recursive filters based on the geodesic distance affinity are realized by two 1D recursions applied in two orthogonal directions of the image plane. The 2D extension of the filter is not valid and has theoretically drawbacks, which lead to known artifacts. In this paper, a maximum influence propagation method is proposed to approximate the 2D extension for the
geodesic distance-based recursive filter. The method allows to partially overcome the drawbacks of the 1D recursion approach. We show that our improved recursion better approximates the true geodesic distance filter, and the application of this improved filter for image denoising outperforms the existing recursive implementation of the geodesic distance. As an application,
we consider a geodesic distance-based filter for image denoising.
Experimental evaluation of our denoising method demonstrates comparable and for several test images better results, than stateof-the-art approaches, while our algorithm is considerably fasterwith computational complexity O(8P).
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Notes LAMP; ISE; 600.120; 600.098; 600.119 Approved no
Call Number Admin @ si @ Moz2017 Serial 2921
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Author Xinhang Song; Shuqiang Jiang; Luis Herranz
Title Multi-Scale Multi-Feature Context Modeling for Scene Recognition in the Semantic Manifold Type Journal Article
Year 2017 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP
Volume (up) 26 Issue 6 Pages 2721-2735
Keywords
Abstract Before the big data era, scene recognition was often approached with two-step inference using localized intermediate representations (objects, topics, and so on). One of such approaches is the semantic manifold (SM), in which patches and images are modeled as points in a semantic probability simplex. Patch models are learned resorting to weak supervision via image labels, which leads to the problem of scene categories co-occurring in this semantic space. Fortunately, each category has its own co-occurrence patterns that are consistent across the images in that category. Thus, discovering and modeling these patterns are critical to improve the recognition performance in this representation. Since the emergence of large data sets, such as ImageNet and Places, these approaches have been relegated in favor of the much more powerful convolutional neural networks (CNNs), which can automatically learn multi-layered representations from the data. In this paper, we address many limitations of the original SM approach and related works. We propose discriminative patch representations using neural networks and further propose a hybrid architecture in which the semantic manifold is built on top of multiscale CNNs. Both representations can be computed significantly faster than the Gaussian mixture models of the original SM. To combine multiple scales, spatial relations, and multiple features, we formulate rich context models using Markov random fields. To solve the optimization problem, we analyze global and local approaches, where a top-down hierarchical algorithm has the best performance. Experimental results show that exploiting different types of contextual relations jointly consistently improves the recognition accuracy.
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Notes LAMP; 600.120 Approved no
Call Number Admin @ si @ SJH2017a Serial 2963
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Author Mikhail Mozerov; Fei Yang; Joost Van de Weijer
Title Sparse Data Interpolation Using the Geodesic Distance Affinity Space Type Journal Article
Year 2019 Publication IEEE Signal Processing Letters Abbreviated Journal SPL
Volume (up) 26 Issue 6 Pages 943 - 947
Keywords
Abstract In this letter, we adapt the geodesic distance-based recursive filter to the sparse data interpolation problem. The proposed technique is general and can be easily applied to any kind of sparse data. We demonstrate its superiority over other interpolation techniques in three experiments for qualitative and quantitative evaluation. In addition, we compare our method with the popular interpolation algorithm presented in the paper on EpicFlow optical flow, which is intuitively motivated by a similar geodesic distance principle. The comparison shows that our algorithm is more accurate and considerably faster than the EpicFlow interpolation technique.
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Notes LAMP; 600.120 Approved no
Call Number Admin @ si @ MYW2019 Serial 3261
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Author Oriol Ramos Terrades; Ernest Valveny
Title A new use of the ridgelets transform for describing linear singularities in images Type Journal Article
Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 27 Issue 6 Pages 587–596
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Abstract
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Notes DAG Approved no
Call Number DAG @ dag @ RaV2006a Serial 635
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Author Jaume Amores; N. Sebe; Petia Radeva
Title Boosting the distance estimation: Application to the K-Nearest Neighbor Classifier Type Journal Article
Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 27 Issue 3 Pages 201–209
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Abstract
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Notes ADAS;MILAB Approved no
Call Number ADAS @ adas @ ASR2006 Serial 643
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Author Fernando Vilariño; Ludmila I. Kuncheva; Petia Radeva
Title ROC curves and video analysis optimization in intestinal capsule endoscopy Type Journal Article
Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 27 Issue 8 Pages 875–881
Keywords ROC curves; Classification; Classifiers ensemble; Detection of intestinal contractions; Imbalanced classes; Wireless capsule endoscopy
Abstract Wireless capsule endoscopy involves inspection of hours of video material by a highly qualified professional. Time episodes corresponding to intestinal contractions, which are of interest to the physician constitute about 1% of the video. The problem is to label automatically time episodes containing contractions so that only a fraction of the video needs inspection. As the classes of contraction and non-contraction images in the video are largely imbalanced, ROC curves are used to optimize the trade-off between false positive and false negative rates. Classifier ensemble methods and simple classifiers were examined. Our results reinforce the claims from recent literature that classifier ensemble methods specifically designed for imbalanced problems have substantial advantages over simple classifiers and standard classifier ensembles. By using ROC curves with the bagging ensemble method the inspection time can be drastically reduced at the expense of a small fraction of missed contractions.
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Area 800 Expedition Conference
Notes MILAB;MV;SIAI Approved no
Call Number BCNPCL @ bcnpcl @ VKR2006; IAM @ iam @ VKR2006 Serial 647
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Author Xavier Otazu; Oriol Pujol
Title Wavelet based approach to cluster analysis. Application on low dimensional data sets Type Journal Article
Year 2006 Publication Pattern Recognition Letters Abbreviated Journal PRL
Volume (up) 27 Issue 14 Pages 1590–1605
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Abstract
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Notes MILAB; CIC; HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ OtP2006 Serial 658
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Author Fadi Dornaika; Angel Sappa
Title A Featureless and Stochastic Approach to On-board Stereo Vision System Pose Type Journal Article
Year 2009 Publication Image and Vision Computing Abbreviated Journal IMAVIS
Volume (up) 27 Issue 9 Pages 1382–1393
Keywords On-board stereo vision system; Pose estimation; Featureless approach; Particle filtering; Image warping
Abstract This paper presents a direct and stochastic technique for real-time estimation of on-board stereo head’s position and orientation. Unlike existing works which rely on feature extraction either in the image domain or in 3D space, our proposed approach directly estimates the unknown parameters from the stream of stereo pairs’ brightness. The pose parameters are tracked using the particle filtering framework which implicitly enforces the smoothness constraints on the estimated parameters. The proposed technique can be used with a driver assistance applications as well as with augmented reality applications. Extended experiments on urban environments with different road geometries are presented. Comparisons with a 3D data-based approach are presented. Moreover, we provide a performance study aiming at evaluating the accuracy of the proposed approach.
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Notes ADAS Approved no
Call Number ADAS @ adas @ DoS2009b Serial 1152
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