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Author Albert Ali Salah; Theo Gevers; Nicu Sebe; Alessandro Vinciarelli edit  openurl
  Title Computer Vision for Ambient Intelligence Type Journal Article
  Year 2011 Publication Journal of Ambient Intelligence and Smart Environments Abbreviated Journal JAISE  
  Volume 3 Issue 3 Pages 187-191  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ SGS2011a Serial 1725  
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Author Arnau Ramisa; Alex Goldhoorn; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras edit  doi
openurl 
  Title Combining Invariant Features and the ALV Homing Method for Autonomous Robot Navigation Based on Panoramas Type Journal Article
  Year 2011 Publication Journal of Intelligent and Robotic Systems Abbreviated Journal JIRC  
  Volume 64 Issue 3-4 Pages 625-649  
  Keywords  
  Abstract Biologically inspired homing methods, such as the Average Landmark Vector, are an interesting solution for local navigation due to its simplicity. However, usually they require a modification of the environment by placing artificial landmarks in order to work reliably. In this paper we combine the Average Landmark Vector with invariant feature points automatically detected in panoramic images to overcome this limitation. The proposed approach has been evaluated first in simulation and, as promising results are found, also in two data sets of panoramas from real world environments.  
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  Publisher Springer Netherlands Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0921-0296 ISBN Medium  
  Area Expedition Conference  
  Notes RV;ADAS Approved no  
  Call Number Admin @ si @ RGA2011 Serial 1728  
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Author Koen E.A. van de Sande; Theo Gevers; Cees G.M. Snoek edit  doi
openurl 
  Title Empowering Visual Categorization with the GPU Type Journal Article
  Year 2011 Publication IEEE Transactions on Multimedia Abbreviated Journal TMM  
  Volume 13 Issue 1 Pages 60-70  
  Keywords  
  Abstract Visual categorization is important to manage large collections of digital images and video, where textual meta-data is often incomplete or simply unavailable. The bag-of-words model has become the most powerful method for visual categorization of images and video. Despite its high accuracy, a severe drawback of this model is its high computational cost. As the trend to increase computational power in newer CPU and GPU architectures is to increase their level of parallelism, exploiting this parallelism becomes an important direction to handle the computational cost of the bag-of-words approach. When optimizing a system based on the bag-of-words approach, the goal is to minimize the time it takes to process batches of images. Additionally, we also consider power usage as an evaluation metric. In this paper, we analyze the bag-of-words model for visual categorization in terms of computational cost and identify two major bottlenecks: the quantization step and the classification step. We address these two bottlenecks by proposing two efficient algorithms for quantization and classification by exploiting the GPU hardware and the CUDA parallel programming model. The algorithms are designed to (1) keep categorization accuracy intact, (2) decompose the problem and (3) give the same numerical results. In the experiments on large scale datasets it is shown that, by using a parallel implementation on the Geforce GTX260 GPU, classifying unseen images is 4.8 times faster than a quad-core CPU version on the Core i7 920, while giving the exact same numerical results. In addition, we show how the algorithms can be generalized to other applications, such as text retrieval and video retrieval. Moreover, when the obtained speedup is used to process extra video frames in a video retrieval benchmark, the accuracy of visual categorization is improved by 29%.  
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  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number Admin @ si @ SGS2011b Serial 1729  
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Author Marina Alberti; Carlo Gatta; Simone Balocco; Francesco Ciompi; Oriol Pujol; Joana Silva; Xavier Carrillo; Petia Radeva edit  doi
isbn  openurl
  Title Automatic Branching Detection in IVUS Sequences Type Conference Article
  Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 6669 Issue Pages 126-133  
  Keywords  
  Abstract Atherosclerosis is a vascular pathology affecting the arterial walls, generally located in specific vessel sites, such as bifurcations. In this paper, for the first time, a fully automatic approach for the detection of bifurcations in IVUS pullback sequences is presented. The method identifies the frames and the angular sectors in which a bifurcation is visible. This goal is achieved by applying a classifier to a set of textural features extracted from each image of an IVUS pullback. A comparison between two state-of-the-art classifiers is performed, AdaBoost and Random Forest. A cross-validation scheme is applied in order to evaluate the performances of the approaches. The obtained results are encouraging, showing a sensitivity of 75% and an accuracy of 94% by using the AdaBoost algorithm.  
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  Publisher Springer Berlin Heidelberg Place of Publication Berlin Editor Jordi Vitria; Joao Miguel Raposo; Mario Hernandez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-21256-7 Medium  
  Area Expedition Conference IbPRIA  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ AGB2011 Serial 1740  
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Author Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin edit  doi
isbn  openurl
  Title Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes Type Book Chapter
  Year 2011 Publication Innovations in Intelligent Image Analysis Abbreviated Journal  
  Volume 339 Issue Pages 7-29  
  Keywords  
  Abstract A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images.  
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  Publisher Springer Berlin Heidelberg Place of Publication Berlin Editor H. Kawasnicka; L.Jain  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1860-949X ISBN 978-3-642-17933-4 Medium  
  Area Expedition Conference  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ ETP2011 Serial 1746  
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Author Fadi Dornaika; Bogdan Raducanu edit  doi
isbn  openurl
  Title Subtle Facial Expression Recognition in Still Images and Videos Type Book Chapter
  Year 2011 Publication Advances in Face Image Analysis: Techniques and Technologies Abbreviated Journal  
  Volume Issue 14 Pages 259-277  
  Keywords  
  Abstract This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM).  
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  Publisher IGI-Global Place of Publication New York, USA Editor Yu-Jin Zhang  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-6152-0991-0 Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ DoR2011 Serial 1751  
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Author Antonio Hernandez; Carlo Gatta; Laura Igual; Sergio Escalera; Petia Radeva edit  openurl
  Title Automatic Angiography Segmentation Based on Improved Graph-cut Type Conference Article
  Year 2011 Publication Jornada TIC Salut Girona Abbreviated Journal  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference TICGI  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ HGI2011 Serial 1754  
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Author Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva edit  openurl
  Title Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder Type Conference Article
  Year 2011 Publication Jornada TIC Salut Girona Abbreviated Journal  
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  ISSN ISBN Medium  
  Area Expedition Conference TICGI  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ IHE2011 Serial 1755  
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Author Jordi Roca; A.Owen; G.Jordan; Y.Ling; C. Alejandro Parraga; A.Hurlbert edit  url
doi  openurl
  Title Inter-individual Variations in Color Naming and the Structure of 3D Color Space Type Abstract
  Year 2011 Publication Journal of Vision Abbreviated Journal VSS  
  Volume 12 Issue 2 Pages 166  
  Keywords  
  Abstract 36.307
Many everyday behavioural uses of color vision depend on color naming ability, which is neither measured nor predicted by most standardized tests of color vision, for either normal or anomalous color vision. Here we demonstrate a new method to quantify color naming ability by deriving a compact computational description of individual 3D color spaces. Methods: Individual observers underwent standardized color vision diagnostic tests (including anomaloscope testing) and a series of custom-made color naming tasks using 500 distinct color samples, either CRT stimuli (“light”-based) or Munsell chips (“surface”-based), with both forced- and free-choice color naming paradigms. For each subject, we defined his/her color solid as the set of 3D convex hulls computed for each basic color category from the relevant collection of categorised points in perceptually uniform CIELAB space. From the parameters of the convex hulls, we derived several indices to characterise the 3D structure of the color solid and its inter-individual variations. Using a reference group of 25 normal trichromats (NT), we defined the degree of normality for the shape, location and overlap of each color region, and the extent of “light”-“surface” agreement. Results: Certain features of color perception emerge from analysis of the average NT color solid, e.g.: (1) the white category is slightly shifted towards blue; and (2) the variability in category border location across NT subjects is asymmetric across color space, with least variability in the blue/green region. Comparisons between individual and average NT indices reveal specific naming “deficits”, e.g.: (1) Category volumes for white, green, brown and grey are expanded for anomalous trichromats and dichromats; and (2) the focal structure of color space is disrupted more in protanopia than other forms of anomalous color vision. The indices both capture the structure of subjective color spaces and allow us to quantify inter-individual differences in color naming ability.
 
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  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 @ ROJ2011 Serial 1758  
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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.  
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  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  
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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  
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  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.  
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  Notes DAG Approved no  
  Call Number Admin @ si @ RRL2011a Serial 1765  
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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  
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  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.  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVII  
  Notes MILAB;HuPBA Approved no  
  Call Number Admin @ si @ CPB2011 Serial 1767  
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Author Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera edit  url
openurl 
  Title Analisis de la Expresion Oral y Gestual en Proyectos Fin de Carrera Via un Sistema de Vision Artificial Type Miscellaneous
  Year 2011 Publication Revista electronica de la asociacion de enseñantes universitarios de la informatica AENUI Abbreviated Journal ReVision  
  Volume 4 Issue 1 Pages 8-18  
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  Abstract La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1989-1199 ISBN Medium  
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  Notes MILAB;HuPBA;MV Approved no  
  Call Number Admin @ si @ PGB2011c Serial 1783  
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Author Sergio Escalera; Alicia Fornes; Oriol Pujol; Josep Llados; Petia Radeva edit  doi
openurl 
  Title Circular Blurred Shape Model for Multiclass Symbol Recognition Type Journal Article
  Year 2011 Publication IEEE Transactions on Systems, Man and Cybernetics (Part B) (IEEE) Abbreviated Journal TSMCB  
  Volume 41 Issue 2 Pages 497-506  
  Keywords  
  Abstract In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1083-4419 ISBN Medium  
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  Notes MILAB; DAG;HuPBA Approved no  
  Call Number Admin @ si @ EFP2011 Serial 1784  
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Author Javier Vazquez edit  openurl
  Title Colour Constancy in Natural Through Colour Naming and Sensor Sharpening Type Book Whole
  Year 2011 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation.
The implementation of this selection criterion strongly relies on the use of a diagonal
model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D.
Several research lines still remain open. One natural extension would be to measure the
effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene.
 
  Address (down)  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Maria Vanrell;Graham D. Finlayson  
  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ Vaz2011a Serial 1785  
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