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Author Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez edit  doi
openurl 
  Title A Coarse-to-fine Approach for fast Deformable Object Detection Type Conference Article
  Year 2011 Publication IEEE conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1353-1360  
  Keywords  
  Abstract  
  Address Colorado Springs; USA  
  Corporate Author (up) 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 CVPR  
  Notes ISE Approved no  
  Call Number Admin @ si @ PVG2011 Serial 1764  
Permanent link to this record
 

 
Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner edit  openurl
  Title Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type Journal
  Year 2011 Publication e-Perimetron Abbreviated Journal ePER  
  Volume 6 Issue 4 Pages 219-229  
  Keywords  
  Abstract By means of computer vision algorithms scanned images of maps are processed in order to extract relevant geographic information from printed coordinate pairs. The meaningful information is then transformed into georeferencing information for each single map sheet, and the complete set is compiled to produce a graphical index sheet for the map series along with relevant metadata. The whole process is fully automated and trained to attain maximum effectivity and throughput.  
  Address  
  Corporate Author (up) 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 Approved no  
  Call Number Admin @ si @ RRL2011a Serial 1765  
Permanent link to this record
 

 
Author Miguel Oliveira; Angel Sappa; V.Santos edit  doi
isbn  openurl
  Title Unsupervised Local Color Correction for Coarsely Registered Images Type Conference Article
  Year 2011 Publication IEEE conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 201-208  
  Keywords  
  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.  
  Address Colorado Springs  
  Corporate Author (up) Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1063-6919 ISBN 978-1-4577-0394-2 Medium  
  Area Expedition Conference CVPR  
  Notes ADAS Approved no  
  Call Number Admin @ si @ OSS2011; ADAS @ adas @ Serial 1766  
Permanent link to this record
 

 
Author Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva edit  url
openurl 
  Title Automatic Key Frames Detection in Intravascular Ultrasound Sequences Type Conference Article
  Year 2011 Publication In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract 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.  
  Address  
  Corporate Author (up) 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 CVII  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPB2011 Serial 1767  
Permanent link to this record
 

 
Author Miguel Reyes; Jose Ramirez Moreno; Juan R Revilla; Petia Radeva; Sergio Escalera edit   pdf
openurl 
  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
  Year 2011 Publication 6th Congreso Iberoamericano de Tecnologia de Apoyo a la Discapacidad Abbreviated Journal  
  Volume Issue Pages 939-944  
  Keywords  
  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.
 
  Address Palma de Mallorca  
  Corporate Author (up) 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 IBERDISCAP  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ RRR2011 Serial 1768  
Permanent link to this record
 

 
Author Antonio Hernandez; Carlo Gatta; Sergio Escalera; Laura Igual; Victoria Martin Yuste; Petia Radeva edit  isbn
openurl 
  Title Accurate and Robust Fully-Automatic QCA: Method and Numerical Validation Type Conference Article
  Year 2011 Publication 14th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 14 Issue 3 Pages 496-503  
  Keywords  
  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%.  
  Address Toronto, Canada  
  Corporate Author (up) Thesis  
  Publisher Springer Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-23625-9 Medium  
  Area Expedition Conference MICCAI  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ HGE2011 Serial 1769  
Permanent link to this record
 

 
Author Victor Ponce; Mario Gorga; Xavier Baro; Sergio Escalera edit  url
doi  isbn
openurl 
  Title Human Behavior Analysis from Video Data Using Bag-of-Gestures Type Conference Article
  Year 2011 Publication 22nd International Joint Conference on Artificial Intelligence Abbreviated Journal  
  Volume 3 Issue Pages 2836-2837  
  Keywords  
  Abstract 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.  
  Address Barcelona  
  Corporate Author (up) 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 978-1-57735-516-8 Medium  
  Area Expedition Conference IJCAI  
  Notes HuPBA;MV Approved no  
  Call Number Admin @ si @ PGB2011b Serial 1770  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera edit  url
isbn  openurl
  Title Introducing the Separability Matrix for Error Correcting Output Codes Coding Type Conference Article
  Year 2011 Publication 10th International conference on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 227-236  
  Keywords  
  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.  
  Address Napoles, Italy  
  Corporate Author (up) Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-21556-8 Medium  
  Area Expedition Conference MCS  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ BPB2011a Serial 1771  
Permanent link to this record
 

 
Author Eloi Puertas; Sergio Escalera; Oriol Pujol edit  openurl
  Title Multi-Class Multi-Scale Stacked Sequential Learning Type Conference Article
  Year 2011 Publication 10th International Conference on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 197-206  
  Keywords  
  Abstract  
  Address Napoles, Italy  
  Corporate Author (up) Thesis  
  Publisher Springer Place of Publication Editor Carlo Sansone; Josef Kittler; Fabio Roli  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MCS  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ PEP2011b Serial 1772  
Permanent link to this record
 

 
Author Xavier Perez; Cecilio Angulo; Sergio Escalera edit  doi
isbn  openurl
  Title Biologically Inspired Path Execution Using SURF Flow in Robot Navigation Type Conference Article
  Year 2011 Publication 11th International Work Conference on Artificial Neural Networks Abbreviated Journal  
  Volume II Issue Pages 581--588  
  Keywords  
  Abstract 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.  
  Address Malaga  
  Corporate Author (up) 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 978-3-642-21497-4 Medium  
  Area Expedition Conference IWANN  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ PAE2011b Serial 1773  
Permanent link to this record
 

 
Author Oscar Amoros; Sergio Escalera; Anna Puig edit  openurl
  Title Adaboost GPU-based Classifier for Direct Volume Rendering Type Conference Article
  Year 2011 Publication International Conference on Computer Graphics Theory and Applications Abbreviated Journal  
  Volume Issue Pages 215-219  
  Keywords  
  Abstract 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.  
  Address Algarve, Portugal  
  Corporate Author (up) 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 GRAPP  
  Notes MILAB; HuPBA Approved no  
  Call Number Admin @ si @ AEP2011 Serial 1774  
Permanent link to this record
 

 
Author Miguel Angel Bautista; Sergio Escalera; Xavier Baro; Oriol Pujol; Jordi Vitria; Petia Radeva edit  openurl
  Title Compact Evolutive Design of Error-Correcting Output Codes. Supervised and Unsupervised Ensemble Methods and Applications Type Conference Article
  Year 2010 Publication European Conference on Machine Learning Abbreviated Journal  
  Volume I Issue Pages 119-128  
  Keywords  
  Abstract  
  Address  
  Corporate Author (up) 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 ECML  
  Notes MILAB; OR;HUPBA;MV Approved no  
  Call Number Admin @ si @ BEB2010 Serial 1775  
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez edit   pdf
doi  openurl
  Title Selective Spatio-Temporal Interest Points Type Journal Article
  Year 2012 Publication Computer Vision and Image Understanding Abbreviated Journal CVIU  
  Volume 116 Issue 3 Pages 396-410  
  Keywords  
  Abstract Recent progress in the field of human action recognition points towards the use of Spatio-TemporalInterestPoints (STIPs) for local descriptor-based recognition strategies. In this paper, we present a novel approach for robust and selective STIP detection, by applying surround suppression combined with local and temporal constraints. This new method is significantly different from existing STIP detection techniques and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-video words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on popular benchmark datasets (KTH and Weizmann), more challenging datasets of complex scenes with background clutter and camera motion (CVC and CMU), movie and YouTube video clips (Hollywood 2 and YouTube), and complex scenes with multiple actors (MSR I and Multi-KTH), validates our approach and show state-of-the-art performance. Due to the unavailability of ground truth action annotation data for the Multi-KTH dataset, we introduce an actor specific spatio-temporal clustering of STIPs to address the problem of automatic action annotation of multiple simultaneous actors. Additionally, we perform cross-data action recognition by training on source datasets (KTH and Weizmann) and testing on completely different and more challenging target datasets (CVC, CMU, MSR I and Multi-KTH). This documents the robustness of our proposed approach in the realistic scenario, using separate training and test datasets, which in general has been a shortcoming in the performance evaluation of human action recognition techniques.  
  Address  
  Corporate Author (up) Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1077-3142 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ CHM2012 Serial 1806  
Permanent link to this record
 

 
Author Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez edit   pdf
url  doi
openurl 
  Title Discriminative Compact Pyramids for Object and Scene Recognition Type Journal Article
  Year 2012 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 45 Issue 4 Pages 1627-1636  
  Keywords  
  Abstract Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets.  
  Address  
  Corporate Author (up) Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0031-3203 ISBN Medium  
  Area Expedition Conference  
  Notes ISE; CAT;CIC Approved no  
  Call Number Admin @ si @ EKW2012 Serial 1807  
Permanent link to this record
 

 
Author Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras edit  url
openurl 
  Title The IIIA30 MObile Robot Object Recognition Datset Type Conference Article
  Year 2011 Publication 11th Portuguese Robotics Open Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract 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.  
  Address Lisboa  
  Corporate Author (up) 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 Robotica  
  Notes RV;ADAS Approved no  
  Call Number Admin @ si @ RAV2011 Serial 1777  
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