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	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	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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
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	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	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
	Title	Multi-scale Stacked Sequential Learning			Type	Conference Article
	Year	2009	Publication	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	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	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
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	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	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
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