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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Approximate Convex Hulls Family for One-Class Cassification |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Workshop on Multiple Classifier Systems |
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6713 |
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Pages |
106-115 |
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Abstract |
In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification. |
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Napoli, Italy |
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Springer Berlin Heidelberg |
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Carlo Sansone; Josef Kittler; Fabio Roli |
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0302-9743 |
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978-3-642-21556-8 |
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MCS |
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MILAB;HuPBA |
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Admin @ si @ CPR2011b |
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1761 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
User Verification From Walking Activity. First Steps Towards a Personal Verification System |
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Conference Article |
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Year |
2011 |
Publication |
1st International Conference on Pervasive and Embedded Computing and Communication Systems |
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Algarve, Portugal |
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PECCS |
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MILAB;HuPBA |
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Admin @ si @ CPR2011c |
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1762 |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
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Title |
A Non-Rigid Feature Extraction Method for Shape Recognition |
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Conference Article |
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Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
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Pages |
987-991 |
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This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. |
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Beijing; China; September 2011 |
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978-0-7695-4520-2 |
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ICDAR |
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DAG |
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Admin @ si @ AFV2011 |
Serial |
1763 |
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Author |
Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez |
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Title |
A Coarse-to-fine Approach for fast Deformable Object Detection |
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Conference Article |
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Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
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1353-1360 |
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Colorado Springs; USA |
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CVPR |
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ISE |
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Admin @ si @ PVG2011 |
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1764 |
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Author |
Miguel Oliveira; Angel Sappa; V.Santos |
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Title |
Unsupervised Local Color Correction for Coarsely Registered Images |
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Conference Article |
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Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
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201-208 |
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Abstract |
The current paper proposes a new parametric local color correction technique. Initially, several color transfer functions are computed from the output of the mean shift color segmentation algorithm. Secondly, color influence maps are calculated. Finally, the contribution of every color transfer function is merged using the weights from the color influence maps. The proposed approach is compared with both global and local color correction approaches. Results show that our method outperforms the technique ranked first in a recent performance evaluation on this topic. Moreover, the proposed approach is computed in about one tenth of the time. |
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Colorado Springs |
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ISSN |
1063-6919 |
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978-1-4577-0394-2 |
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CVPR |
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ADAS |
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Admin @ si @ OSS2011; ADAS @ adas @ |
Serial |
1766 |
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Author |
Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva |
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Title |
Automatic Key Frames Detection in Intravascular Ultrasound Sequences |
Type |
Conference Article |
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Year |
2011 |
Publication |
In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging |
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We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events. |
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CVII |
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Notes |
MILAB;HuPBA |
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Call Number |
Admin @ si @ CPB2011 |
Serial |
1767 |
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Author |
Miguel Reyes; Jose Ramirez Moreno; Juan R Revilla; Petia Radeva; Sergio Escalera |
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Title |
ADiBAS: Sistema Multisensor de Adquisicion Automatica de Datos Corporales Objetivos, Robustos y Fiables para el Analisis de la Postura y el Movimiento |
Type |
Conference Article |
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Year |
2011 |
Publication |
6th Congreso Iberoamericano de Tecnologia de Apoyo a la Discapacidad |
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Pages |
939-944 |
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Abstract |
El análisis de la postura y del rango de movimiento son fundamentales para conocer la optimización del gesto y mejorar, de este modo, el rendimiento y la detección de posibles lesiones. Esta cuantificación es especialmente interesante en deportistas o en pacientes que presentan alguna lesión neurológica o del sistema musculo-esquelético, ya que permite conocer el proceso evolutivo de estos pacientes, evaluar la eficacia de la terapia aplicada y proponer, en caso necesario, una modificación del protocolo de tratamiento.
En este trabajo presentamos un sistema automático que permite, mediante una tecnología no invasiva, la captación automática de marcadores LED situados sobre el paciente y su posterior análisis con el fin de mostrar al especialista datos objetivos que permitan un mejor soporte diagnóstico. También se describe un
sistema analítico de la postura corporal sin marcadores, donde su ejecución durante secuencias dinámicas aporta un alto grado de naturalidad al paciente a la hora de realizar los ejercicios funcionales. |
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Address |
Palma de Mallorca |
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Conference |
IBERDISCAP |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ RRR2011 |
Serial |
1768 |
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Author |
Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva |
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Title |
Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Medical Image Computing and Computer Assisted Intervention |
Abbreviated Journal |
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Volume |
14 |
Issue |
3 |
Pages |
496-503 |
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Abstract |
The Quantitative Coronary Angiography (QCA) is a methodology used to evaluate the arterial diseases and, in particular, the degree of stenosis. In this paper we propose AQCA, a fully automatic method for vessel segmentation based on graph cut theory. Vesselness, geodesic paths and a new multi-scale edgeness map are used to compute a globally optimal artery segmentation. We evaluate the method performance in a rigorous numerical way on two datasets. The method can detect an artery with precision 92.9 +/- 5% and sensitivity 94.2 +/- 6%. The average absolute distance error between detected and ground truth centerline is 1.13 +/- 0.11 pixels (about 0.27 +/- 0.025 mm) and the absolute relative error in the vessel caliber estimation is 2.93% with almost no bias. Moreover, the method can discriminate between arteries and catheter with an accuracy of 96.4%. |
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Toronto, Canada |
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Springer |
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978-3-642-23625-9 |
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MICCAI |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ HGE2011 |
Serial |
1769 |
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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Sergio Escalera |
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Title |
Human Behavior Analysis from Video Data Using Bag-of-Gestures |
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Conference Article |
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Year |
2011 |
Publication |
22nd International Joint Conference on Artificial Intelligence |
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3 |
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2836-2837 |
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Human Behavior Analysis in Uncontrolled Environments can be categorized in two main challenges: 1) Feature extraction and 2) Behavior analysis from a set of corporal language vocabulary. In this work, we present our achievements characterizing some simple behaviors from visual data on different real applications and discuss our plan for future work: low level vocabulary definition from bag-of-gesture units and high level modelling and inference of human behaviors. |
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Barcelona |
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978-1-57735-516-8 |
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IJCAI |
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HuPBA;MV |
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Call Number |
Admin @ si @ PGB2011b |
Serial |
1770 |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
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227-236 |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Springer-Verlag Berlin Heidelberg |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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978-3-642-21556-8 |
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MILAB; OR;HuPBA;MV |
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Admin @ si @ BPB2011a |
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1771 |
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Author |
Eloi Puertas; Sergio Escalera; Oriol Pujol |
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Title |
Multi-Class Multi-Scale Stacked Sequential Learning |
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Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
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6713 |
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197-206 |
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Napoles, Italy |
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Springer |
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Carlo Sansone; Josef Kittler; Fabio Roli |
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HuPBA;MILAB |
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Admin @ si @ PEP2011b |
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1772 |
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Author |
Xavier Perez; Cecilio Angulo; Sergio Escalera |
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Title |
Biologically Inspired Path Execution Using SURF Flow in Robot Navigation |
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Conference Article |
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Year |
2011 |
Publication |
11th International Work Conference on Artificial Neural Networks |
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II |
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581--588 |
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An exportable and robust system using only camera images is proposed for path execution in robot navigation. Motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames, so the method is called SURF flow. This information is used to correct robot displacement when a straight forward path command is sent to the robot, but it is not really executed due to several robot and environmental concerns. The proposed system has been successfully tested on the legged robot Aibo. |
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Malaga |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-21497-4 |
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IWANN |
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HuPBA;MILAB |
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Admin @ si @ PAE2011b |
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1773 |
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Author |
Oscar Amoros; Sergio Escalera; Anna Puig |
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Title |
Adaboost GPU-based Classifier for Direct Volume Rendering |
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Conference Article |
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Year |
2011 |
Publication |
International Conference on Computer Graphics Theory and Applications |
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215-219 |
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In volume visualization, the voxel visibitity and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges. |
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Algarve, Portugal |
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GRAPP |
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MILAB; HuPBA |
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no |
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Call Number |
Admin @ si @ AEP2011 |
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1774 |
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Author |
Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva |
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Title |
Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications |
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Conference Article |
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2010 |
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European Conference on Machine Learning |
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I |
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119-128 |
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MILAB; OR;HUPBA;MV |
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Admin @ si @ BEB2010 |
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1775 |
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Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
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The IIIA30 MObile Robot Object Recognition Datset |
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2011 |
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11th Portuguese Robotics Open |
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Object perception is a key feature in order to make mobile robots able to perform high-level tasks. However, research aimed at addressing the constraints and limitations encountered in a mobile robotics scenario, like low image resolution, motion blur or tight computational constraints, is still very scarce. In order to facilitate future research in this direction, in this work we present an object detection and recognition dataset acquired using a mobile robotic platform. As a baseline for the dataset, we evaluated the cascade of weak classifiers object detection method from Viola and Jones. |
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Lisboa |
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Robotica |
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RV;ADAS |
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Admin @ si @ RAV2011 |
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1777 |
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