|   | 
Details
   web
Records
Author Maria Salamo; Sergio Escalera; Petia Radeva
Title Quality Enhancement based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender Type Conference Article
Year 2009 Publication 8th International Conference on Case-Based Reasoning Abbreviated Journal
Volume (down) 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 Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; Horst Bunke
Title A Recursive Embedding Approach to Median Graph Computation Type Conference Article
Year 2009 Publication 7th IAPR – TC–15 Workshop on Graph–Based Representations in Pattern Recognition Abbreviated Journal
Volume (down) 5534 Issue Pages 113–123
Keywords
Abstract The median graph has been shown to be a good choice to infer a representative of a set of graphs. It has been successfully applied to graph-based classification and clustering. Nevertheless, its computation is extremely complex. Several approaches have been presented up to now based on different strategies. In this paper we present a new approximate recursive algorithm for median graph computation based on graph embedding into vector spaces. Preliminary experiments on three databases show that this new approach is able to obtain better medians than the previous existing approaches.
Address Venice, Italy
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-02123-7 Medium
Area Expedition Conference GBR
Notes DAG Approved no
Call Number DAG @ dag @ FKV2009 Serial 1173
Permanent link to this record
 

 
Author Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi
Title Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging Type Conference Article
Year 2009 Publication 5th International Conference on Functional Imaging and Modeling of the Heart Abbreviated Journal
Volume (down) 5528 Issue Pages 330–338
Keywords
Abstract In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm).
Address Nice, 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 978-3-642-01931-9 Medium
Area Expedition Conference FIMH
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ COP2009 Serial 1255
Permanent link to this record
 

 
Author Carlo Gatta; Juan Diego Gomez; Francesco Ciompi; O. Rodriguez-Leor; Petia Radeva
Title Toward robust myocardial blush grade estimation in contrast angiography Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages 249–256
Keywords
Abstract The assessment of Myocardial Blush Grade after primary angioplasty is a precious diagnostic tool to understand if the patient needs further medication or the use of specifics drugs. Unfortunately, the assessment of MBG is difficult for non highly specialized staff. Experimental data show that there is poor correlation between MBG assessment of low and high specialized staff, thus reducing its applicability. This paper proposes a method able to achieve an objective measure of MBG, or a set of parameters that correlates with the MBG. The method tracks the blush area starting from just one single frame tagged by the physician. As a consequence, the blush area is kept isolated from contaminating phenomena such as diaphragm and arteries movements. We also present a method to extract four parameters that are expected to correlate with the MBG. Preliminary results show that the method is capable of extracting interesting information regarding the behavior of the myocardial perfusion.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ GGC2009 Serial 1161
Permanent link to this record
 

 
Author Francesco Ciompi; Oriol Pujol; O. Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva
Title Enhancing In-Vitro IVUS Data for Tissue Characterization Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages 241–248
Keywords
Abstract Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPR2009a Serial 1162
Permanent link to this record
 

 
Author Miquel Ferrer; Ernest Valveny; F. Serratosa
Title Median Graph Computation by means of a Genetic Approach Based on Minimum Common Supergraph and Maximum Common Subraph Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages 346–353
Keywords
Abstract Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present a new genetic algorithm for the median graph computation. A set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity, show that we obtain good approximations of the median graph. Finally, we use the median graph in a real nearest neighbour classification showing that it leaves the box of the only-theoretical concepts and demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number DAG @ dag @ FVS2009c Serial 1174
Permanent link to this record
 

 
Author Albert Gordo; Ernest Valveny
Title The diagonal split: A pre-segmentation step for page layout analysis & classification Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages 290–297
Keywords
Abstract Document classification is an important task in all the processes related to document storage and retrieval. In the case of complex documents, structural features are needed to achieve a correct classification. Unfortunately, physical layout analysis is error prone. In this paper we present a pre-segmentation step based on a divide & conquer strategy that can be used to improve the page segmentation results, independently of the segmentation algorithm used. This pre-segmentation step is evaluated in classification and retrieval using the selective CRLA algorithm for layout segmentation together with a clustering based on the voronoi area diagram, and tested on two different databases, MARG and Girona Archives.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes DAG Approved no
Call Number DAG @ dag @ Gov2009b Serial 1176
Permanent link to this record
 

 
Author Pierluigi Casale; Oriol Pujol; Petia Radeva
Title Face-to-face social activity detection using data collected with a wearable device Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages 56–63
Keywords
Abstract In this work the feasibility of building a socially aware badge that learns from user activities is explored. A wearable multisensor device has been prototyped for collecting data about user movements and photos of the environment where the user acts. Using motion data, speaking and other activities have been classified. Images have been analysed in order to complement motion data and help for the detection of social behaviours. A face detector and an activity classifier are both used for detecting if users have a social activity in the time they worn the device. Good results encourage the improvement of the system at both hardware and software level
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes MILAB;HuPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPR2009b Serial 1206
Permanent link to this record
 

 
Author Marco Pedersoli; Jordi Gonzalez; Juan J. Villanueva
Title High-Speed Human Detection Using a Multiresolution Cascade of Histograms of Oriented Gradients Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages
Keywords
Abstract This paper presents a new method for human detection based on a multiresolution cascade of Histograms of Oriented Gradients (HOG) that can highly reduce the computational cost of the detection search without affecting accuracy. The method consists of a cascade of sliding window detectors. Each detector is a Support Vector Machine (SVM) composed by features at different resolution, from coarse for the first level to fine for the last one.
Considering that the spatial stride of the sliding window search is affected by the HOG features size, unlike previous methods based on Adaboost cascades, we can adopt a spatial stride inversely proportional to the features resolution. This produces that the speed-up of the cascade is not only due to the low number of features that need to be computed in the first levels, but also to the lower number of detection windows that needs to be evaluated.
Experimental results shows that our method permits a detection rate comparable with the state of the art, but at the same time a gain in the speed of the detection search of 10-20 times depending on the cascade configuration.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number ISE @ ise @ PGV2009 Serial 1214
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez
Title Towards Real-Time Human Action Recognition Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages
Keywords
Abstract This work presents a novel approach to human detection based action-recognition in real-time. To realize this goal our method first detects humans in different poses using a correlation-based approach. Recognition of actions is done afterward based on the change of the angular values subtended by various body parts. Real-time human detection and action recognition are very challenging, and most state-of-the-art approaches employ complex feature extraction and classification techniques, which ultimately becomes a handicap for real-time recognition. Our correlation-based method, on the other hand, is computationally efficient and uses very simple gradient-based features. For action recognition angular features of body parts are extracted using a skeleton technique. Results for action recognition are comparable with the present state-of-the-art.
Address Póvoa de Varzim, Portugal
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number DAG @ dag @ CBG2009 Serial 1215
Permanent link to this record
 

 
Author Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca
Title Robust and Efficient Multipose Face Detection Using Skin Color Segmentation Type Conference Article
Year 2009 Publication 4th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume (down) 5524 Issue Pages
Keywords
Abstract In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches.
Address Springer Berlin Heidelberg
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 978-3-642-02171-8 Medium
Area Expedition Conference IbPRIA
Notes ISE Approved no
Call Number DAG @ dag @ ABG2009 Serial 1216
Permanent link to this record
 

 
Author Sergio Escalera; Oriol Pujol; Petia Radeva
Title Recoding Error-Correcting Output Codes Type Conference Article
Year 2009 Publication 8th International Workshop of Multiple Classifier Systems Abbreviated Journal
Volume (down) 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
Title Multi-scale Stacked Sequential Learning Type Conference Article
Year 2009 Publication 8th International Workshop of Multiple Classifier Systems Abbreviated Journal
Volume (down) 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
Permanent link to this record
 

 
Author Bogdan Raducanu; Fadi Dornaika
Title Dynamic Vs. Static Recognition of Facial Expressions Type Book Chapter
Year 2008 Publication Ambient Intelligence. European Conference Abbreviated Journal
Volume (down) 5355 Issue Pages 13–25
Keywords
Abstract
Address Nuremberg (Germany)
Corporate Author Thesis
Publisher Place of Publication Editor Rabuñal
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference AMI
Notes OR; MV Approved no
Call Number BCNPCL @ bcnpcl @ RaD2008 Serial 1035
Permanent link to this record
 

 
Author Miquel Ferrer; Ernest Valveny; F. Serratosa; Horst Bunke
Title Exact Median Graph Computation via Graph Embedding Type Conference Article
Year 2008 Publication 12th International Workshop on Structural and Syntactic Pattern Recognition Abbreviated Journal
Volume (down) 5324 Issue Pages 15–24
Keywords
Abstract
Address Orlando – Florida (USA)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference SSPR
Notes DAG Approved no
Call Number DAG @ dag @ FVS2008b Serial 1076
Permanent link to this record