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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  
Permanent link to this record
 

 
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  
Permanent link to this record
 

 
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 S. Chanda; Umapada Pal; Oriol Ramos Terrades edit  doi
openurl 
  Title Word-Wise Thai and Roman Script Identification Type Journal
  Year 2009 Publication (up) ACM Transactions on Asian Language Information Processing Abbreviated Journal TALIP  
  Volume 8 Issue 3 Pages 1-21  
  Keywords  
  Abstract In some Thai documents, a single text line of a printed document page may contain words of both Thai and Roman scripts. For the Optical Character Recognition (OCR) of such a document page it is better to identify, at first, Thai and Roman script portions and then to use individual OCR systems of the respective scripts on these identified portions. In this article, an SVM-based method is proposed for identification of word-wise printed Roman and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of a character group combining different character features obtained from structural shape, profile behavior, component overlapping information, topological properties, and water reservoir concept, etc. Based on the experiment on 10,000 data (words) we obtained 99.62% script identification accuracy from the proposed scheme.  
  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 1530-0226 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ CPR2009f Serial 1869  
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Author Arnau Ramisa; Adriana Tapus; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras edit  doi
openurl 
  Title Robust Vision-Based Localization using Combinations of Local Feature Regions Detectors Type Journal Article
  Year 2009 Publication (up) Autonomous Robots Abbreviated Journal AR  
  Volume 27 Issue 4 Pages 373-385  
  Keywords  
  Abstract This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°.
In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization.
 
  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 0929-5593 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number Admin @ si @ RTA2009 Serial 1245  
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Author Ferran Diego; Daniel Ponsa; Joan Serrat; Antonio Lopez edit  openurl
  Title Video alignment for automotive applications Type Miscellaneous
  Year 2009 Publication (up) BMVA one–day technical meeting on vision for automotive applications Abbreviated Journal  
  Volume Issue Pages  
  Keywords video alignment  
  Abstract  
  Address London, UK  
  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 @ DPS2009 Serial 1271  
Permanent link to this record
 

 
Author Jose Manuel Alvarez; Antonio Lopez edit  openurl
  Title Model-based road detection using shadowless features and on-line learning Type Miscellaneous
  Year 2009 Publication (up) BMVA one–day technical meeting on vision for automotive applications Abbreviated Journal  
  Volume Issue Pages  
  Keywords road detection  
  Abstract  
  Address London, UK  
  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 @ AlA2009 Serial 1272  
Permanent link to this record
 

 
Author Pau Baiget; Carles Fernandez; Xavier Roca; Jordi Gonzalez edit  doi
openurl 
  Title Generation of Augmented Video Sequences Combining Behavioral Animation and Multi Object Tracking Type Journal Article
  Year 2009 Publication (up) Computer Animation and Virtual Worlds Abbreviated Journal  
  Volume 20 Issue 4 Pages 473–489  
  Keywords  
  Abstract In this paper we present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior-based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd.

We present a novel approach to generate augmented video sequences in real-time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi-object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. © 2009 Wiley Periodicals, Inc.
 
  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 ISE Approved no  
  Call Number ISE @ ise @ BFR2009 Serial 1170  
Permanent link to this record
 

 
Author David Vazquez; David Geronimo; Antonio Lopez edit   pdf
openurl 
  Title The effect of the distance in pedestrian detection Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 149 Issue Pages  
  Keywords Pedestrian Detection  
  Abstract Pedestrian accidents are one of the leading preventable causes of death. In order to reduce the number of accidents, in the last decade the pedestrian protection systems have been introduced, a special type of advanced driver assistance systems, in witch an on-board camera explores the road ahead for possible collisions with pedestrians in order to warn the driver or perform braking actions. As a result of the variability of the appearance, pose and size, pedestrian detection is a very challenging task. So many techniques, models and features have been proposed to solve the problem. As the appearance of pedestrians varies signi cantly as a function of distance, a system based on multiple classi ers specialized on diferent depths is likely to improve the overall performance with respect to a typical system based on a general detector. Accordingly, the main aim of this work is to explore the e ect of the distance in pedestrian detection. We have evaluated three pedestrian detectors (HOG, HAAR and EOH) in two di erent databases (INRIA and Daimler09) for two di erent sizes (small and big). By a extensive set of experiments we answer to questions like which datasets and evaluation methods are the most adequate, which is the best method for each size of the pedestrians and why or how do the method optimum parameters vary with respect to the distance  
  Address  
  Corporate Author Thesis Master's thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference M.Sc.  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ VGL2009 Serial 1669  
Permanent link to this record
 

 
Author Albert Andaluz edit   pdf
openurl 
  Title LV Contour Segmentation in TMR images using Semantic Description of Tissue and Prior Knowledge Correction Type Report
  Year 2009 Publication (up) 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 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  
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Author Mohammad Rouhani edit  openurl
  Title 3D Data Fitting and Tracking for Real Time Applications Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 138 Issue 138 Pages  
  Keywords  
  Abstract  
  Address Barcelona, Spain  
  Corporate Author Thesis Master's thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes invisible;ADAS Approved no  
  Call Number Admin @ si @ Rou2009 Serial 1150  
Permanent link to this record
 

 
Author Hany Salah Eldeen edit  openurl
  Title Colour Naming in Context through a Perceptual Model Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 130 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Bellaterra, Barcelona 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 @ Eld2009 Serial 2389  
Permanent link to this record
 

 
Author Naila Murray edit  openurl
  Title Perceptual Feature Detection Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 131 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Bellaterra, Barcelona 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 Admin @ si @ Mur2009 Serial 2390  
Permanent link to this record
 

 
Author Josep M. Gonfaus edit  openurl
  Title Semantic Segmentation of Images Using Random Ferns Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 132 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Bellaterra, Barcelona 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 ISE Approved no  
  Call Number Admin @ si @ Gon2009 Serial 2391  
Permanent link to this record
 

 
Author Albert Gordo edit  openurl
  Title A Cyclic Page Layout Descriptor for Document Classification & Retrieval Type Report
  Year 2009 Publication (up) CVC Technical Report Abbreviated Journal  
  Volume 128 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Bellaterra, Barcelona 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;DAG Approved no  
  Call Number Admin @ si @ Gor2009 Serial 2387  
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