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Author C. Alejandro Parraga; Jordi Roca; Maria Vanrell edit  url
doi  openurl
  Title Do Basic Colors Influence Chromatic Adaptation? Type Journal Article
  Year 2011 Publication Journal of Vision Abbreviated Journal VSS  
  Volume 11 Issue 11 Pages 85  
  Keywords  
  Abstract Color constancy (the ability to perceive colors relatively stable under different illuminants) is the result of several mechanisms spread across different neural levels and responding to several visual scene cues. It is usually measured by estimating the perceived color of a grey patch under an illuminant change. In this work, we hypothesize whether chromatic adaptation (without a reference white or grey) could be driven by certain colors, specifically those corresponding to the universal color terms proposed by Berlin and Kay (1969). To this end we have developed a new psychophysical paradigm in which subjects adjust the color of a test patch (in CIELab space) to match their memory of the best example of a given color chosen from the universal terms list (grey, red, green, blue, yellow, purple, pink, orange and brown). The test patch is embedded inside a Mondrian image and presented on a calibrated CRT screen inside a dark cabin. All subjects were trained to “recall” their most exemplary colors reliably from memory and asked to always produce the same basic colors when required under several adaptation conditions. These include achromatic and colored Mondrian backgrounds, under a simulated D65 illuminant and several colored illuminants. A set of basic colors were measured for each subject under neutral conditions (achromatic background and D65 illuminant) and used as “reference” for the rest of the experiment. The colors adjusted by the subjects in each adaptation condition were compared to the reference colors under the corresponding illuminant and a “constancy index” was obtained for each of them. Our results show that for some colors the constancy index was better than for grey. The set of best adapted colors in each condition were common to a majority of subjects and were dependent on the chromaticity of the illuminant and the chromatic background considered.  
  Address  
  Corporate Author (down) Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1534-7362 ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ PRV2011 Serial 1759  
Permanent link to this record
 

 
Author Mario Rojas; David Masip; Jordi Vitria edit  doi
isbn  openurl
  Title Predicting Dominance Judgements Automatically: A Machine Learning Approach. Type Conference Article
  Year 2011 Publication IEEE International Workshop on Social Behavior Analysis Abbreviated Journal  
  Volume Issue Pages 939-944  
  Keywords  
  Abstract The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task.  
  Address Santa Barbara, CA  
  Corporate Author (down) 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 978-1-4244-9140-7 Medium  
  Area Expedition Conference SBA  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ RMV2011b Serial 1760  
Permanent link to this record
 

 
Author Pierluigi Casale; Oriol Pujol; Petia Radeva edit  url
doi  isbn
openurl 
  Title Approximate Convex Hulls Family for One-Class Cassification Type Conference Article
  Year 2011 Publication 10th International Workshop on Multiple Classifier Systems Abbreviated Journal  
  Volume 6713 Issue Pages 106-115  
  Keywords  
  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.  
  Address Napoli, Italy  
  Corporate Author (down) Thesis  
  Publisher Springer 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 0302-9743 ISBN 978-3-642-21556-8 Medium  
  Area Expedition Conference MCS  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPR2011b Serial 1761  
Permanent link to this record
 

 
Author Pierluigi Casale; Oriol Pujol; Petia Radeva edit  openurl
  Title User Verification From Walking Activity. First Steps Towards a Personal Verification System Type Conference Article
  Year 2011 Publication 1st International Conference on Pervasive and Embedded Computing and Communication Systems Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Algarve, Portugal  
  Corporate Author (down) 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 PECCS  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPR2011c Serial 1762  
Permanent link to this record
 

 
Author Jon Almazan; Alicia Fornes; Ernest Valveny edit  url
doi  isbn
openurl 
  Title A Non-Rigid Feature Extraction Method for Shape Recognition Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 987-991  
  Keywords  
  Abstract 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.  
  Address Beijing; China; September 2011  
  Corporate Author (down) 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 978-0-7695-4520-2 Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ AFV2011 Serial 1763  
Permanent link to this record
 

 
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 (down) 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 (down) 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 (down) 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 (down) 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 (down) 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 (down) 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 (down) 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 (down) 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 (down) 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 Sala; 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 (down) 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  
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