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Author  |
Oriol Pujol; Debora Gil; Petia Radeva |
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Title |
Fundamentals of Stop and Go active models |
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Journal Article |
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Year |
2005 |
Publication |
Image and Vision Computing |
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Volume |
23 |
Issue |
8 |
Pages |
681-691 |
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Keywords |
Deformable models; Geodesic snakes; Region-based segmentation |
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Abstract |
An efficient snake formulation should conform to the idea of picking the smoothest curve among all the shapes approximating an object of interest. In current geodesic snakes, the regularizing curvature also affects the convergence stage, hindering the latter at concave regions. In the present work, we make use of characteristic functions to define a novel geodesic formulation that decouples regularity and convergence. This term decoupling endows the snake with higher adaptability to non-convex shapes. Convergence is ensured by splitting the definition of the external force into an attractive vector field and a repulsive one. In our paper, we propose to use likelihood maps as approximation of characteristic functions of object appearance. The better efficiency and accuracy of our decoupled scheme are illustrated in the particular case of feature space-based segmentation. |
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Butterworth-Heinemann |
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Newton, MA, USA |
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0262-8856 |
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IAM;MILAB;HuPBA |
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IAM @ iam @ PGR2005 |
Serial |
1629 |
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Author |
Oriol Pujol; Eloi Puertas; Carlo Gatta |
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Title |
Multi-scale Stacked Sequential Learning |
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Conference Article |
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Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
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5519 |
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Pages |
262–271 |
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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. |
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Reykjavik, Iceland |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02325-5 |
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MCS |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PPG2009 |
Serial |
1260 |
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Author |
Oriol Pujol; Misael Rosales; Petia Radeva; E Fernandez-Nofrerias |
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Title |
Intravascular Ultrasound Images Vessel Characterization using AdaBoost |
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Miscellaneous |
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Year |
2003 |
Publication |
Proceedings on FIMH |
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Lyon, France |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PRR2003a |
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400 |
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Author |
Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; E. Fernandez; V. Valle; Petia Radeva |
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Title |
Automatic segmentation and characterization of IVUS images by texture analysis |
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Miscellaneous |
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2004 |
Publication |
European Society of Cardiology Congress 2004 |
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Munich |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PRM2004 |
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478 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Lumen Detection in Ivus Image Using Snakes in a Statical Framework. |
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Miscellaneous |
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Year |
2002 |
Publication |
XX Congreso Anual de la Sociedad Española de Ingenieria Biomedica CASEIB 2002, 1: 129–132. |
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Saragossa, Espanya |
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MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ PuR2002 |
Serial |
315 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Texture Segmentation by Statistic Deformable Models |
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Year |
2003 |
Publication |
International Journal of Image and Graphics (IJIG) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2003 |
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432 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Texture Segmentation by Statistical Deformable Models |
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Year |
2004 |
Publication |
International Journal of Image and Graphics |
Abbreviated Journal |
IJIG |
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Volume |
4 |
Issue |
3 |
Pages |
433-452 |
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Keywords |
Texture segmentation, parametric active contours, statistic snakes |
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Abstract |
Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2004a |
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505 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Solving Particularization with Supervised Clustering Competition Scheme |
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2005 |
Publication |
Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3523: 11–18 |
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Estoril (Portugal) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2005b |
Serial |
557 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
On the assessment of texture descriptors in intravascular ultrasound images: A boosting approach to a feasible plaque classification |
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2005 |
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Plaque Imaging: Pixel to Molecular Level, IOS Press, J. Suri et al. (Eds.), 113: 276–299, ISBN: 1–58603–516–9 |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PuR2005a |
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563 |
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Author |
Oriol Pujol; Petia Radeva |
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Title |
Optimal extension of Error Correcting Output Codes |
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Miscellaneous |
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2006 |
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Perpignan (France) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ EPR2006d |
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695 |
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Author |
Oriol Pujol; Petia Radeva; J. Mauri; E Fernandez-Nofrerias |
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Title |
Automatic segmentation of lumen in Intravascular Ultrasound Images: An evaluation of texture feature extractors. |
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Miscellaneous |
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2002 |
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Iberoamerican Conference on Artificial Intelligence IBERAMIA 2002, Springer Verlag |
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Sevilla, Espanya |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ PRM2002 |
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314 |
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Author |
Oriol Pujol; Petia Radeva; Jordi Vitria |
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Title |
Traffic sign recognition using an adaptive boosting multiclass framework |
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2005 |
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Workshop sobre Reconocimiento de Formas y Analisis de Imagenes (AERFAI), I Congreso Español de Informatica (CEDI´2005) |
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Granada (Spain) |
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OR;MILAB;HuPBA;MV |
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BCNPCL @ bcnpcl @ PRV2005 |
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618 |
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Oriol Pujol; Petia Radeva; Jordi Vitria |
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Title |
Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes |
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2006 |
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6): 1007–1012 |
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BCNPCL @ bcnpcl @ PRV2006a |
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646 |
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Oriol Pujol; Petia Radeva; Jordi Vitria; J. Mauri |
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Adaboost to Classify Plaque Appearance in IVUS Images |
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2004 |
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Progress in Pattern Recognition, Image Analysis and Applications, LNCS 3287:629–636 |
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Puebla (Mexico) |
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BCNPCL @ bcnpcl @ PRV2004 |
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472 |
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Oriol Pujol; Sergio Escalera; Petia Radeva |
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An Incremental Node Embedding Technique for Error Correcting Output Codes |
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2008 |
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Pattern Recognition |
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41 |
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2 |
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713–725 |
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BCNPCL @ bcnpcl @ PER2008 |
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942 |
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