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Author Bhaskar Chakraborty; Ognjen Rudovic; Jordi Gonzalez edit  openurl
  Title View-Invariant Human-Body Detection with Extension to Human Action Recognition using Component-Wise HMM of Body Parts Type Conference Article
  Year 2008 Publication (up) 8th IEEE International Conference on Automatic Face and Gesture Recognition Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Amsterdam; The Netherlands  
  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 FG  
  Notes ISE Approved no  
  Call Number ISE @ ise @ CRG2008 Serial 1113  
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Author Mohammad Rouhani; Angel Sappa edit  doi
isbn  openurl
  Title A Novel Approach to Geometric Fitting of Implicit Quadrics Type Conference Article
  Year 2009 Publication (up) 8th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal  
  Volume 5807 Issue Pages 121–132  
  Keywords  
  Abstract This paper presents a novel approach for estimating the geometric distance from a given point to the corresponding implicit quadric curve/surface. The proposed estimation is based on the height of a tetrahedron, which is used as a coarse but reliable estimation of the real distance. The estimated distance is then used for finding the best set of quadric parameters, by means of the Levenberg-Marquardt algorithm, which is a common framework in other geometric fitting approaches. Comparisons of the proposed approach with previous ones are provided to show both improvements in CPU time as well as in the accuracy of the obtained results.  
  Address Bordeaux, France  
  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 978-3-642-04696-4 Medium  
  Area Expedition Conference ACIVS  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ RoS2009 Serial 1194  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title Rigid and Non-Rigid Face Motion Tracking by Aligning Texture Maps and Stereo-Based 3D Models Type Book Chapter
  Year 2006 Publication (up) 8th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS´06), LNCS 4179: 675–684 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Antwerp (Belgium)  
  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 @ DoS2006c Serial 689  
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Author Maria Salamo; Sergio Escalera; Petia Radeva edit  doi
isbn  openurl
  Title Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender Type Conference Article
  Year 2009 Publication (up) 8th International Conference on Case-Based Reasoning Abbreviated Journal  
  Volume 5650 Issue Pages 298–312  
  Keywords  
  Abstract Personalizing the product recommendation task is a major focus of research in the area of conversational recommender systems. Conversational case-based recommender systems help users to navigate through product spaces, alternatively making product suggestions and eliciting users feedback. Critiquing is a common form of feedback and incremental critiquing-based recommender system has shown its efficiency to personalize products based primarily on a quality measure. This quality measure influences the recommendation process and it is obtained by the combination of compatibility and similarity scores. In this paper, we describe new compatibility strategies whose basis is on reinforcement learning and a new feature weighting technique which is based on the user’s history of critiques. Moreover, we show that our methodology can significantly improve recommendation efficiency in comparison with the state-of-the-art approaches.  
  Address Seattle, USA  
  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 978-3-642-02998-1 Medium  
  Area Expedition Conference ICCBR  
  Notes HuPBA; MILAB Approved no  
  Call Number BCNPCL @ bcnpcl @ SER2009 Serial 1187  
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Author Zhong Jin; Franck Davoine edit  openurl
  Title Orthogonal ICA Representation Of Images Type Miscellaneous
  Year 2004 Publication (up) 8th International Conference on Control, Automation, Robotics and Vision, 369–374 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Kunming (China)  
  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 Approved no  
  Call Number Admin @ si @ JiD2004 Serial 499  
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Author Oriol Ramos Terrades; Ernest Valveny edit  openurl
  Title Local Norm Features based on ridgelets Transform Type Miscellaneous
  Year 2005 Publication (up) 8th International Conference on Document Analysis and Recognition (ICDAR´05), 700–704 Abbreviated Journal  
  Volume Issue Pages  
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  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  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RaV2005d Serial 642  
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Author Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera edit   pdf
openurl 
  Title Three-Dimensional Design of Error Correcting Output Codes Type Conference Article
  Year 2012 Publication (up) 8th International Conference on Machine Learning and Data Mining Abbreviated Journal  
  Volume Issue Pages 29-  
  Keywords  
  Abstract  
  Address Berlin, Germany  
  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 MLDM  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ BGE2012a Serial 2041  
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Author Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda edit   pdf
openurl 
  Title ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos Type Miscellaneous
  Year 2014 Publication (up) 8th International Congress on University Teaching and Innovation Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Tarragona; juliol 2014  
  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 CIDUI  
  Notes IAM; ADAS; 600.076; 600.063; 600.075 Approved no  
  Call Number Admin @ si @ MGG2014 Serial 2457  
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Author Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil edit   pdf
openurl 
  Title Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías Type Miscellaneous
  Year 2014 Publication (up) 8th International Congress on University Teaching and Innovation Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Tarragona; juliol 2014  
  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 CIDUI  
  Notes IAM; 600.075;DAG Approved no  
  Call Number Admin @ si @ SRM2014 Serial 2458  
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Author Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) edit  isbn
openurl 
  Title Graphics Recognition: Achievements, Challenges, and Evolution Type Book Whole
  Year 2010 Publication (up) 8th International Workshop GREC 2009. Abbreviated Journal  
  Volume 6020 Issue Pages  
  Keywords  
  Abstract  
  Address La Rochelle  
  Corporate Author Thesis  
  Publisher Springer Link Place of Publication Editor Jean-Marc Ogier; Wenyin Liu; Josep Llados  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-13727-3 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ OLL2010 Serial 1976  
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Author Sergio Escalera; Oriol Pujol; Petia Radeva edit  doi
isbn  openurl
  Title Recoding Error-Correcting Output Codes Type Conference Article
  Year 2009 Publication (up) 8th International Workshop of Multiple Classifier Systems Abbreviated Journal  
  Volume 5519 Issue Pages 11–21  
  Keywords  
  Abstract One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design.  
  Address Reykjavik (Iceland)  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02325-5 Medium  
  Area Expedition Conference MCS  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2009d Serial 1190  
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Author Oriol Pujol; Eloi Puertas; Carlo Gatta edit  doi
isbn  openurl
  Title Multi-scale Stacked Sequential Learning Type Conference Article
  Year 2009 Publication (up) 8th International Workshop of Multiple Classifier Systems Abbreviated Journal  
  Volume 5519 Issue Pages 262–271  
  Keywords  
  Abstract One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions.  
  Address Reykjavik, Iceland  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-02325-5 Medium  
  Area Expedition Conference MCS  
  Notes MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ PPG2009 Serial 1260  
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Author Rain Eric Haamer; Kaustubh Kulkarni; Nasrin Imanpour; Mohammad Ahsanul Haque; Egils Avots; Michelle Breisch; Kamal Nasrollahi; Sergio Escalera; Cagri Ozcinar; Xavier Baro; Ahmad R. Naghsh-Nilchi; Thomas B. Moeslund; Gholamreza Anbarjafari edit   pdf
doi  openurl
  Title Changes in Facial Expression as Biometric: A Database and Benchmarks of Identification Type Conference Article
  Year 2018 Publication (up) 8th International Workshop on Human Behavior Understanding Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Facial dynamics can be considered as unique signatures for discrimination between people. These have started to become important topic since many devices have the possibility of unlocking using face recognition or verification. In this work, we evaluate the efficacy of the transition frames of video in emotion as compared to the peak emotion frames for identification. For experiments with transition frames we extract features from each frame of the video from a fine-tuned VGG-Face Convolutional Neural Network (CNN) and geometric features from facial landmark points. To model the temporal context of the transition frames we train a Long-Short Term Memory (LSTM) on the geometric and the CNN features. Furthermore, we employ two fusion strategies: first, an early fusion, in which the geometric and the CNN features are stacked and fed to the LSTM. Second, a late fusion, in which the prediction of the LSTMs, trained independently on the two features, are stacked and used with a Support Vector Machine (SVM). Experimental results show that the late fusion strategy gives the best results and the transition frames give better identification results as compared to the peak emotion frames.  
  Address Xian; China; May 2018  
  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 FGW  
  Notes HUPBA; no proj Approved no  
  Call Number Admin @ si @ HKI2018 Serial 3118  
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Author Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti edit   pdf
url  doi
openurl 
  Title Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy Type Conference Article
  Year 2010 Publication (up) 8th Medical Imaging Abbreviated Journal  
  Volume 7623 Issue 762304 Pages 304  
  Keywords  
  Abstract Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.  
  Address  
  Corporate Author Thesis  
  Publisher SPIE 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 SPIE  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGH2010a Serial 1522  
Permanent link to this record
 

 
Author Debora Gil; Jaume Garcia; Mariano Vazquez; Ruth Aris; Guilleaume Houzeaux edit   pdf
isbn  openurl
  Title Patient-Sensitive Anatomic and Functional 3D Model of the Left Ventricle Function Type Conference Article
  Year 2008 Publication (up) 8th World Congress on Computational Mechanichs (WCCM8) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Left Ventricle, Electromechanical Models, Image Processing, Magnetic Resonance.  
  Abstract Early diagnosis and accurate treatment of Left Ventricle (LV) dysfunction significantly increases the patient survival. Impairment of LV contractility due to cardiovascular diseases is reflected in its motion patterns. Recent advances in medical imaging, such as Magnetic Resonance (MR), have encouraged research on 3D simulation and modelling of the LV dynamics. Most of the existing 3D models [1] consider just the gross anatomy of the LV and restore a truncated ellipse which deforms along the cardiac cycle. The contraction mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fibers. It follows that such simplified models do not allow evaluation of the heart electro-mechanical function and coupling, which has recently risen as the key point for understanding the LV functionality [2]. In order to thoroughly understand the LV mechanics it is necessary to consider the complete anatomy of the LV given by the orientation of the myocardial fibres in 3D space as described by Torrent Guasp [3].
We propose developing a 3D patient-sensitive model of the LV integrating, for the first time, the ven- tricular band anatomy (fibers orientation), the LV gross anatomy and its functionality. Such model will represent the LV function as a natural consequence of its own ventricular band anatomy. This might be decisive in restoring a proper LV contraction in patients undergoing pace marker treatment.
The LV function is defined as soon as the propagation of the contractile electromechanical pulse has been modelled. In our experiments we have used the wave equation for the propagation of the electric pulse. The electromechanical wave moves on the myocardial surface and should have a conductivity tensor oriented along the muscular fibers. Thus, whatever mathematical model for electric pulse propa- gation [4] we consider, the complete anatomy of the LV should be extracted.
The LV gross anatomy is obtained by processing multi slice MR images recorded for each patient. Information about the myocardial fibers distribution can only be extracted by Diffusion Tensor Imag- ing (DTI), which can not provide in vivo information for each patient. As a first approach, we have
Figure 1: Scheme for the Left Ventricle Patient-Sensitive Model.
computed an average model of fibers from several DTI studies of canine hearts. This rough anatomy is the input for our electro-mechanical propagation model simulating LV dynamics. The average fiber orientation is updated until the simulated LV motion agrees with the experimental evidence provided by the LV motion observed in tagged MR (TMR) sequences. Experimental LV motion is recovered by applying image processing, differential geometry and interpolation techniques to 2D TMR slices [5]. The pipeline in figure 1 outlines the interaction between simulations and experimental data leading to our patient-tailored model.
 
  Address Venice; Italy  
  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 9788496736559 Medium  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ GGV2008b Serial 993  
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