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Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera |
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Title |
Compact Evolutive Design of Error-Correcting Output Codes |
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Conference Article |
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Year |
2010 |
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Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases |
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119-128 |
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Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization |
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The classication of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classiers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classiers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classiers. Evolutionary computation is used for tuning the parameters of the classiers and looking for the best Minimal ECOC code conguration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers. |
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Barcelona (Spain) |
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SUEMA |
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OR;MILAB;HUPBA;MV |
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BCNPCL @ bcnpcl @ BBP2010 |
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1363 |
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Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; H. Tizon; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Radial Artery Volume Changes After Administration Of Two Different Intra-arterial Drug Regimens. Assessment by Intravascular Ultrasound |
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Journal Article |
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2010 |
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Journal of the American College of Cardiology |
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JACC |
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56 |
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13s1 |
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B119 |
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MILAB |
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BCNPCL @ bcnpcl @ SFC2010b |
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1364 |
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Francesco Ciompi; Oriol Pujol; Petia Radeva |
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Title |
A meta-learning approach to Conditional Random Fields using Error-Correcting Output Codes |
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2010 |
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20th International Conference on Pattern Recognition |
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710–713 |
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We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a classification problem where margin classifiers are used. The set of state transitions for the edge potential is treated as a set of different classes, thus defining a multi-class learning problem. The Error-Correcting Output Codes (ECOC) technique is used to deal with the multi-class problem. Furthermore, the point defined by the combination of margin classifiers in the ECOC space is interpreted in a probabilistic manner, and the obtained distance values are then converted into potential values. The proposed model exhibits very promising results when applied to two real detection problems. |
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Istanbul;Turkey |
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1051-4651 |
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978-1-4244-7542-1 |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ CPR2010a |
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1365 |
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Jose Seabra; F. Javier Sanchez; Francesco Ciompi; Petia Radeva |
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Title |
Ultrasonographic Plaque Characterization using a Rayleigh Mixture Model |
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Conference Article |
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2010 |
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7th IEEE International Symposium on Biomedical Imaging |
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1–4 |
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From Nano to Macro
A correct modelling of tissue morphology is determinant for the identification of vulnerable plaques. This paper aims at describing the plaque composition by means of a Rayleigh Mixture Model applied to ultrasonic data. The effectiveness of using a mixture of distributions is established through synthetic and real ultrasonic data samples. Furthermore, the proposed mixture model is used in a plaque classification problem in Intravascular Ultrasound (IVUS) images of coronary plaques. A classifier tested on a set of 67 in-vitro plaques, yields an overall accuracy of 86% and sensitivity of 92%, 94% and 82%, for fibrotic, calcified and lipidic tissues, respectively. These results strongly suggest that different plaques types can be distinguished by means of the coefficients and Rayleigh parameters of the mixture distribution. |
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Rotterdam (Netherlands) |
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1945-7928 |
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978-1-4244-4125-9 |
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ISBI |
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MILAB |
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BCNPCL @ bcnpcl @ SSC2010 |
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1366 |
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Neus Salvatella; E Fernandez-Nofrerias; Francesco Ciompi; Oriol Rodriguez-Leor; Xavier Carrillo; R. Hemetsberger; Petia Radeva; J. Mauri; A. Bayes |
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Title |
Canvis de volum a la arteria radial despres de la administracio de dos tractaments vasodilatadors. Avaluacio mitjançant ecografia intravascular |
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Conference Article |
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2010 |
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22nd Congres Societat Catalana de Cardiologia, |
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179 |
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Barcelona (Spain) |
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MILAB |
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BCNPCL @ bcnpcl @ SFC2010a |
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1367 |
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Oriol Rodriguez-Leor; R. Hemetsberger; Francesco Ciompi; E Fernandez-Nofrerias; Angel Serrano; M. Bernet; Petia Radeva; J. Mauri; A. Bayes |
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Title |
Caracteritzacio automatica de la placa mitjançant analisis del espectre de radiofreqüencia en estudi de ecografia intracoronaria: resultat de la fusio de dades invivo i exvivo |
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Conference Article |
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2010 |
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22nd Congres Societat Catalana de Cardiologia, |
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131 |
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Barcelona (Spain) |
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MILAB |
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BCNPCL @ bcnpcl @ RHC2010 |
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1368 |
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R. de Nijs; Sebastian Ramos; Gemma Roig; Xavier Boix; Luc Van Gool; K. Kühnlenz. |
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Title |
On-line Semantic Perception Using Uncertainty |
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Conference Article |
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2012 |
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International Conference on Intelligent Robots and Systems |
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IROS |
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4185-4191 |
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Semantic Segmentation |
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Visual perception capabilities are still highly unreliable in unconstrained settings, and solutions might not beaccurate in all regions of an image. Awareness of the uncertainty of perception is a fundamental requirement for proper high level decision making in a robotic system. Yet, the uncertainty measure is often sacrificed to account for dependencies between object/region classifiers. This is the case of Conditional Random Fields (CRFs), the success of which stems from their ability to infer the most likely world configuration, but they do not directly allow to estimate the uncertainty of the solution. In this paper, we consider the setting of assigning semantic labels to the pixels of an image sequence. Instead of using a CRF, we employ a Perturb-and-MAP Random Field, a recently introduced probabilistic model that allows performing fast approximate sampling from its probability density function. This allows to effectively compute the uncertainty of the solution, indicating the reliability of the most likely labeling in each region of the image. We report results on the CamVid dataset, a standard benchmark for semantic labeling of urban image sequences. In our experiments, we show the benefits of exploiting the uncertainty by putting more computational effort on the regions of the image that are less reliable, and use more efficient techniques for other regions, showing little decrease of performance |
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IROS |
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ADAS |
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ADAS @ adas @ NRR2012 |
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2378 |
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Author |
Daniel Ponsa; Joan Serrat; Antonio Lopez |
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Title |
On-board image-based vehicle detection and tracking |
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2011 |
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Transactions of the Institute of Measurement and Control |
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TIM |
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33 |
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7 |
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783-805 |
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vehicle detection |
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In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time. |
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ADAS |
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ADAS @ adas @ PSL2011 |
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1413 |
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Author |
David Geronimo; Antonio Lopez |
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Title |
Deteccion de Peatones para Sistemas Avanzados de Asistencia al Conductor |
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Miscellaneous |
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2010 |
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UAB Divulga |
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Los sistemas de asistencia al conductor, y particularmente los sistemas de protección de peatones, representan uno de los campos de investigación más activos dedicados a la mejora de la seguridad vial. El mayor desafío es el desarrollo de sistemas a bordo fiables de detección de peatones. En esta revisión del estado de la técnica de la detección de peatones, se divide el problema en diferentes etapas, cada una con responsabilidades propias dentro del sistema. Esta división facilita el posterior análisis y discusión de cada uno de los métodos en la literatura, favoreciendo la comparación entre ellos. Finalmente se discuten los temas más importantes de este campo poniendo especial énfasis en las necesidades actuales y los desafíos futuros. |
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Bellaterra (Catalonia), Spain |
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spreading;ADAS |
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ADAS @ adas @ GeL2010a |
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1414 |
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Author |
David Augusto Rojas; Fahad Shahbaz Khan; Joost Van de Weijer |
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Title |
The Impact of Color on Bag-of-Words based Object Recognition |
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Conference Article |
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2010 |
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20th International Conference on Pattern Recognition |
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1549–1553 |
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In recent years several works have aimed at exploiting color information in order to improve the bag-of-words based image representation. There are two stages in which color information can be applied in the bag-of-words framework. Firstly, feature detection can be improved by choosing highly informative color-based regions. Secondly, feature description, typically focusing on shape, can be improved with a color description of the local patches. Although both approaches have been shown to improve results the combined merits have not yet been analyzed. Therefore, in this paper we investigate the combined contribution of color to both the feature detection and extraction stages. Experiments performed on two challenging data sets, namely Flower and Pascal VOC 2009; clearly demonstrate that incorporating color in both feature detection and extraction significantly improves the overall performance. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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CAT @ cat @ RKW2010 |
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1415 |
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Author |
Jaume Gibert; Ernest Valveny |
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Title |
Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. |
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Conference Article |
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2010 |
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13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition |
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6218 |
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223–232 |
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Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster. |
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Springer Berlin Heidelberg |
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In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano, |
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LNCS |
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0302-9743 |
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978-3-642-14979-5 |
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S+SSPR |
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DAG |
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DAG @ dag @ GiV2010 |
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1416 |
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David Aldavert; Arnau Ramisa; Ramon Lopez de Mantaras; Ricardo Toledo |
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Title |
Real-time Object Segmentation using a Bag of Features Approach |
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Conference Article |
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2010 |
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13th International Conference of the Catalan Association for Artificial Intelligence |
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220 |
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321–329 |
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Object Segmentation; Bag Of Features; Feature Quantization; Densely sampled descriptors |
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In this paper, we propose an object segmentation framework, based on the popular bag of features (BoF), which can process several images per second while achieving a good segmentation accuracy assigning an object category to every pixel of the image. We propose an efficient color descriptor to complement the information obtained by a typical gradient-based local descriptor. Results show that color proves to be a useful cue to increase the segmentation accuracy, specially in large homogeneous regions. Then, we extend the Hierarchical K-Means codebook using the recently proposed Vector of Locally Aggregated Descriptors method. Finally, we show that the BoF method can be easily parallelized since it is applied locally, thus the time necessary to process an image is further reduced. The performance of the proposed method is evaluated in the standard PASCAL 2007 Segmentation Challenge object segmentation dataset. |
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IOS Press Amsterdam, |
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In R.Alquezar, A.Moreno, J.Aguilar. |
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9781607506423 |
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CCIA |
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no |
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Call Number |
Admin @ si @ ARL2010b |
Serial |
1417 |
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Author |
Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca |
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Title |
Reactive object tracking with a single PTZ camera |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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Pages |
1690–1693 |
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In this paper we describe a novel approach to reactive tracking of moving targets with a pan-tilt-zoom camera. The approach uses an extended Kalman filter to jointly track the object position in the real world, its velocity in 3D and the camera intrinsics, in addition to the rate of change of these parameters. The filter outputs are used as inputs to PID controllers which continuously adjust the camera motion in order to reactively track the object at a constant image velocity while simultaneously maintaining a desirable target scale in the image plane. We provide experimental results on simulated and real tracking sequences to show how our tracker is able to accurately estimate both 3D object position and camera intrinsics with very high precision over a wide range of focal lengths. |
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Istanbul (Turkey) |
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ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
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ICPR |
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ISE |
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no |
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Call Number |
DAG @ dag @ ABG2010 |
Serial |
1418 |
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Author |
Anjan Dutta; Umapada Pal; Alicia Fornes; Josep Llados |
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Title |
An Efficient Staff Removal Technique from Printed Musical Documents |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
1965–1968 |
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Abstract |
Staff removal is an important preprocessing step of the Optical Music Recognition (OMR). The process aims to remove the stafflines from a musical document and retain only the musical symbols, later these symbols are used effectively to identify the music information. This paper proposes a simple but robust method to remove stafflines from printed musical scores. In the proposed methodology we have considered a staffline segment as a horizontal linkage of vertical black runs with uniform height. We have used the neighbouring properties of a staffline segment to validate it as a true segment. We have considered the dataset along with the deformations described in for evaluation purpose. From experimentation we have got encouraging results. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG |
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no |
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Call Number |
DAG @ dag @ DPF2010 |
Serial |
1420 |
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Author |
Alicia Fornes; Sergio Escalera; Josep Llados; Ernest Valveny |
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Title |
Symbol Classification using Dynamic Aligned Shape Descriptor |
Type |
Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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Pages |
1957–1960 |
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Abstract |
Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we propose a new descriptor and distance computation for coping with the problem of symbol recognition in the domain of Graphical Document Image Analysis. The proposed D-Shape descriptor encodes the arrangement information of object parts in a circular structure, allowing different levels of distortion. The classification is performed using a cyclic Dynamic Time Warping based method, allowing distortions and rotation. The methodology has been validated on different data sets, showing very high recognition rates. |
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Istanbul (Turkey) |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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Notes |
DAG; HUPBA; MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ FEL2010 |
Serial |
1421 |
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Permanent link to this record |