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	Author	Debora Gil; Petia Radeva
	Title	Inhibition of False Landmarks			Type	Book Chapter
	Year	2004	Publication	Recent Advances in Artificial Intelligence Research and Development	Abbreviated Journal
	Volume		Issue		Pages	233-244
	Keywords
	Abstract	We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication	Barcelona (Spain)	Editor	al, J.V. et
	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;MILAB			Approved	no
	Call Number	IAM @ iam @ GiR2004a			Serial	1533
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	Author	F.Guirado; Ana Ripoll; C.Roig; Aura Hernandez-Sabate; Emilio Luque
	Title	Exploiting Throughput for Pipeline Execution in Streaming Image Processing Applications			Type	Book Chapter
	Year	2006	Publication	Euro-Par 2006 Parallel Processing	Abbreviated Journal	LNCS
	Volume	4128	Issue		Pages	1095-1105
	Keywords	12th International Euro–Par Conference
	Abstract	There is a large range of image processing applications that act on an input sequence of image frames that are continuously received. Throughput is a key performance measure to be optimized when execu- ting them. In this paper we propose a new task replication methodology for optimizing throughput for an image processing application in the field of medicine. The results show that by applying the proposed methodo- logy we are able to achieve the desired throughput in all cases, in such a way that the input frames can be processed at any given rate.
	Address
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin Heidelberg	Place of Publication	Dresden, Germany (European Union)	Editor	UAB; W, E.N.; et al.
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes In Computer Science	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	Euro–Par
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ GRR2006a			Serial	1542
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	Author	Ole Vilhelm-Larsen; Petia Radeva; Enric Marti
	Title	Guidelines for choosing optimal parameters of elasticity for snakes			Type	Book Chapter
	Year	1995	Publication	Computer Analysis Of Images And Patterns	Abbreviated Journal	LNCS
	Volume	970	Issue		Pages	106-113
	Keywords
	Abstract	This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
	Address
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	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		Medium
	Area		Expedition		Conference
	Notes	MILAB;IAM			Approved	no
	Call Number	IAM @ iam @ LRM1995b			Serial	1558
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	Author	Josep Llados; Jaime Lopez-Krahe; Enric Marti
	Title	A system to understand hand-drawn floor plans using subgraph isomorphism and Hough transform			Type	Book Chapter
	Year	1997	Publication	Machine Vision and Applications	Abbreviated Journal
	Volume	10	Issue	3	Pages	150-158
	Keywords	Line drawings – Hough transform – Graph matching – CAD systems – Graphics recognition
	Abstract	Presently, man-machine interface development is a widespread research activity. A system to understand hand drawn architectural drawings in a CAD environment is presented in this paper. To understand a document, we have to identify its building elements and their structural properties. An attributed graph structure is chosen as a symbolic representation of the input document and the patterns to recognize in it. An inexact subgraph isomorphism procedure using relaxation labeling techniques is performed. In this paper we focus on how to speed up the matching. There is a building element, the walls, characterized by a hatching pattern. Using a straight line Hough transform (SLHT)-based method, we recognize this pattern, characterized by parallel straight lines, and remove from the input graph the edges belonging to this pattern. The isomorphism is then applied to the remainder of the input graph. When all the building elements have been recognized, the document is redrawn, correcting the inaccurate strokes obtained from a hand-drawn input.
	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;IAM			Approved	no
	Call Number	IAM @ iam @ LLM1997a			Serial	1566
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	Author	Josep Llados; Gemma Sanchez; Enric Marti
	Title	A string based method to recognize symbols and structural textures in architectural plans			Type	Book Chapter
	Year	1998	Publication	Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers	Abbreviated Journal	LNCS
	Volume	1389	Issue	1998	Pages	91-103
	Keywords
	Abstract	This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.
	Address
	Corporate Author				Thesis
	Publisher	Springer Link	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	LNCS	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG; IAM			Approved	no
	Call Number	IAM @ iam @ SLE1998			Serial	1573
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	Author	Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil
	Title	Suppression of IVUS Image Rotation. A Kinematic Approach			Type	Book Chapter
	Year	2005	Publication	Functional Imaging and Modeling of the Heart	Abbreviated Journal	LNCS
	Volume	3504	Issue		Pages	889-892
	Keywords
	Abstract	IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin / Heidelberg	Place of Publication		Editor	Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume	3504	Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM;MILAB			Approved	no
	Call Number	IAM @ iam @ RRR2005			Serial	1645
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	Author	Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke
	Title	Writer Identification in Old Handwritten Music Scores			Type	Book Chapter
	Year	2012	Publication	Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology	Abbreviated Journal
	Volume		Issue		Pages	27-63
	Keywords
	Abstract	The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%.
	Address
	Corporate Author				Thesis
	Publisher	IGI-Global	Place of Publication		Editor	Copnstantin Papaodysseus
	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	Admin @ si @ FLS2012			Serial	1828
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	Author	Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus
	Title	Color Naming			Type	Book Chapter
	Year	2012	Publication	Color in Computer Vision: Fundamentals and Applications	Abbreviated Journal
	Volume		Issue	17	Pages	287-317
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	John Wiley & Sons, Ltd.	Place of Publication		Editor	Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek
	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 @ WBV2012			Serial	2063
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	Author	Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo
	Title	Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models			Type	Book Chapter
	Year	2012	Publication	Vision Robotics: Technologies for Machine Learning and Vision Applications	Abbreviated Journal
	Volume		Issue	2	Pages	23-42
	Keywords
	Abstract	Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis.
	Address
	Corporate Author				Thesis
	Publisher	IGI-Global	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	MILAB;HuPBA			Approved	no
	Call Number	Admin @ si @ PIE2012			Serial	2064
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	Author	Fadi Dornaika; Bogdan Raducanu
	Title	Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation			Type	Book Chapter
	Year	2012	Publication	Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions	Abbreviated Journal
	Volume		Issue		Pages	157-178
	Keywords
	Abstract
	Address
	Corporate Author				Thesis
	Publisher	NOVA Publishers	Place of Publication		Editor	S.E. Carter
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MV			Approved	no
	Call Number	Admin @ si @ DoR2012			Serial	2183
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	Author	Fadi Dornaika; Bogdan Raducanu; Alireza Bosaghzadeh
	Title	Facial expression recognition based on multi observations with application to social robotics			Type	Book Chapter
	Year	2015	Publication	Emotional and Facial Expressions: Recognition, Developmental Differences and Social Importance	Abbreviated Journal
	Volume		Issue		Pages	153-166
	Keywords
	Abstract	Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this chapter, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, viewand texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial expression.
	Address
	Corporate Author				Thesis
	Publisher	Nova Science publishers	Place of Publication		Editor	Bruce Flores
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	LAMP;			Approved	no
	Call Number	Admin @ si @ DRB2015			Serial	2720
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	Author	Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal
	Title	3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos			Type	Book Chapter
	Year	2015	Publication	Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015	Abbreviated Journal
	Volume	9515	Issue		Pages	140-152
	Keywords	Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
	Abstract	Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select those image regions presenting the highest stable spatio-temporal response. Spatio-temporal stability is achieved by extracting 3D watershed regions on the temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
	Address
	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	CARE
	Notes	IAM; MV; 600.075			Approved	no
	Call Number	Admin @ si @ GSF2015			Serial	2733
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	Author	Jordina Torrents-Barrena; Aida Valls; Petia Radeva; Meritxell Arenas; Domenec Puig
	Title	Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis			Type	Book Chapter
	Year	2015	Publication	Artificial Intelligence Research and Development	Abbreviated Journal
	Volume	277	Issue		Pages	247 - 256
	Keywords
	Abstract	Breast cancer disease has recently been classified into four subtypes regarding the molecular properties of the affected tumor region. For each patient, an accurate diagnosis of the specific type is vital to decide the most appropriate therapy in order to enhance life prospects. Nowadays, advanced therapeutic diagnosis research is focused on gene selection methods, which are not robust enough. Hence, we hypothesize that computer vision algorithms can offer benefits to address the problem of discriminating among them through X-Ray images. In this paper, we propose a novel approach driven by texture feature descriptors and machine learning techniques. First, we segment the tumour part through an active contour technique and then, we perform a complete fractal analysis to collect qualitative information of the region of interest in the feature extraction stage. Finally, several supervised and unsupervised classifiers are used to perform multiclass classification of the aforementioned data. The experimental results presented in this paper support that it is possible to establish a relation between each tumor subtype and the extracted features of the patterns revealed on mammograms.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	Frontiers in Artificial Intelligence and Applications	Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @TVR2015			Serial	2780
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	Author	Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel
	Title	An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres			Type	Book Chapter
	Year	2015	Publication	The White Book on Public Library Network from Diputació de Barcelona	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	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	MV; DAG;SIAI			Approved	no
	Call Number	Admin @ si @VKC2015			Serial	2798
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	Author	Pedro Herruzo; Marc Bolaños; Petia Radeva
	Title	Can a CNN Recognize Catalan Diet?			Type	Book Chapter
	Year	2016	Publication	AIP Conference Proceedings	Abbreviated Journal
	Volume	1773	Issue		Pages
	Keywords
	Abstract	CoRR abs/1607.08811 Nowadays, we can find several diseases related to the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, these diseases are related to the food consumption of people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent many metabolic diseases. In particular, our work focuses on the recognition of Mediterranean food and dishes. The development of this methodology would allow to analise the daily habits of users with wearable cameras, within the topic of lifelogging. By using automatic mechanisms we could build an objective tool for the analysis of the patient’s behavior, allowing specialists to discover unhealthy food patterns and understand the user’s lifestyle. With the aim to automatically recognize a complete diet, we introduce a challenging multi-labeled dataset related to Mediter-ranean diet called FoodCAT. The first type of label provided consists of 115 food classes with an average of 400 images per dish, and the second one consists of 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet recognition. In this context, deep learning and more specifically, Convolutional Neural Networks (CNNs), currently are state-of-the-art methods for automatic food recognition. In our work, we compare several architectures for image classification, with the purpose of diet recognition. Applying the best model for recognising food categories, we achieve a top-1 accuracy of 72.29%, and top-5 of 97.07%. In a complete diet recognition of dishes from Mediterranean diet, enlarged with the Food-101 dataset for international dishes recognition, we achieve a top-1 accuracy of 68.07%, and top-5 of 89.53%, for a total of 115+101 food classes.
	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	MILAB			Approved	no
	Call Number	Admin @ si @ HBR2016			Serial	2837
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