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  • Image Segmentation Evaluation and Its Application to Object Detection

     Pont Tuset, Jordi
    Defense's date: 2014-02-19
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    Les primeres parts d'aquesta Tesi se centren en l'estudi de l'avaluació supervisada d'algorismes de segmentació d'imatges. Supervisada en el sentit que els resultats de la segmentació es comparen amb una anotació feta per un humà, coneguda com a ground truth, per mitjà de diferents mesures de similitud. L'avaluació depèn, per tant, de tres punts principals.En primer lloc, les tècniques de segmentació d'imatge que s'avaluen. Es revisa l'estat de l'art en la segmentació de la imatge, fent una diferència explícita entre aquestes tècniques que proporcionen una sortida plana, és a dir, una única agrupació del conjunt de píxels en regions, i les que produeixen una segmentació jeràrquica, és a dir, una estructura en forma d'arbre que representa les regions a diferents escales, des dels detalls fins la imatge completa.En segon lloc, les bases de dades de ground truth són de summa importància en l'avaluació. Es poden dividir en les anotades només a nivell d'objecte, és a dir, amb conjunts de píxels marcats que es refereixen a objectes que no cobreixen tota la imatge; o les que tenen particions completes anotades, que proporcionen una agrupació completa de tots els píxels d'una imatge. Depenent del tipus de base de dades es diu que l'anàlisi es fa des d'una perspectiva objecte o des d'una perspectiva de partició.Finalment, les mesures de similitud utilitzades per comparar els resultats generats amb el ground truth és el que ens proporcionarà una eina quantitativa per avaluar si els resultats són bons, i de quina manera es poden millorar. Les principals aportacions de les primeres parts de la tesi són en el camp de les mesures de similitud.En primer lloc, des d'un punt de vista d'objecte, es revisen les mesures bàsiques que s'utilitzen per comparar dues representacions d'objectes i es demostra que algunes d'elles són equivalents. Per tal d'avaluar les particions completes i jerarquies contra un objecte, cal seleccionar quines de les seves regions formen l'objecte a avaluar. Revisem i millorem aquestes tècniques per mitjà d'un model matemàtic del problema. Aquesta anàlisi ens permet mostrar que les jerarquies poden representar objectes molt millor amb molt menys nombre de regions que les particions planes.Des de la perspectiva de partició, la literatura sobre les mesures d'avaluació és extensa i complexa. La nostra primera contribució és revisar, estructurar i deduplicar les mesures disponibles. Presentem una nova mesura que es demostra que millora les anteriors en termes d'un conjunt de meta-mesures qualitatives i quantitatives. També estenem les mesures sobre les particions planes per avaluar segmentacions jeràrquiques.L'última part d'aquesta Tesi progressa des de l'avaluació de la segmentació d'imatges cap a la seva aplicació a la detecció d'objectes. En particular, ens basem en algunes de les conclusions extretes en la primera part per generar candidats d'objectes segmentats. Donat un conjunt de jerarquies, construïm els parells i triplets de regions, aprenem a combinar el conjunt de cada jerarquia i a prioritzar-los segons descriptors de baix i mig nivell. Duem a terme una extensa validació experimental que mostra que el nostre mètode supera l'estat de l'art en moltes mètriques analitzades.

  • Improving retrieval accuracy of Hierarchical Cellular Trees for generic metric spaces

     Ventura Royo, Carles; Vilaplana Besler, Veronica; Giro Nieto, Xavier; Marques Acosta, Fernando
    Multimedia tools and applications
    Date of publication: 2013-09
    Journal article

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    Metric Access Methods (MAMs) are indexing techniques which allow working in generic metric spaces. Therefore, MAMs are specially useful for Content- Based Image Retrieval systems based on features which use non Lp norms as similarity measures. MAMs naturally allow the design of image browsers due to their inherent hierarchical structure. The Hierarchical Cellular Tree (HCT), a MAM-based indexing technique, provides the starting point of our work. In this paper, we describe some limitations detected in the original formulation of the HCT and propose some modifications to both the index building and the search algorithm. First, the covering radius, which is defined as the distance from the representative to the furthest element in a node, may not cover all the elements belonging to the node¿s subtree. Therefore, we propose to redefine the covering radius as the distance from the representative to the furthest element in the node¿s subtree. This new definition is essential to guarantee a correct construction of the HCT. Second, the proposed Progressive Query retrieval scheme can be redesigned to perform the nearest neighbor operation in a more efficient way. We propose a new retrieval scheme which takes advantage of the benefits of the search algorithm used in the index building. Furthermore, while the evaluation of the HCT in the original work was only subjective, we propose an objective evaluation based on two aspects which are crucial in any approximate search algorithm: the retrieval time and the retrieval accuracy. Finally, we illustrate the usefulness of the proposal by presenting some actual applications.

    Abstract Metric Access Methods (MAMs) are indexing techniques which al- low working in generic metric spaces. Therefore, MAMs are specially useful for Content-Based Image Retrieval systems based on features which use non Lp norms as similarity measures. MAMs naturally allow the design of image browsers due to their inherent hierarchical structure. The Hierarchical Cellular Tree (HCT), a MAM-based indexing technique, provides the starting point of our work. In this paper, we describe some limitations detected in the original formulation of the HCT and propose some modi cations to both the index building and the search algorithm. First, the covering radius, which is de ned as the distance from the representative to the furthest element in a node, may not cover all the elements belonging to the node's subtree. Therefore, we pro- pose to rede ne the covering radius as the distance from the representative to the furthest element in the node's subtree. This new de nition is essen- tial to guarantee a correct construction of the HCT. Second, the proposed Progressive Query retrieval scheme can be redesigned to perform the nearest neighbor operation in a more e cient way. We propose a new retrieval scheme which takes advantage of the bene ts of the search algorithm used in the index building. Furthermore, while the evaluation of the HCT in the original work was only subjective, we propose an objective evaluation based on two aspects which are crucial in any approximate search algorithm: the retrieval time and the retrieval accuracy. Finally, we illustrate the usefulness of the proposal by presenting some actual applications.

  • Salient object detection on a hierarchy of image partitions

     Vilaplana Besler, Veronica; Muntaner Perello, Guillermo
    IEEE International Conference on Image Processing
    Presentation's date: 2013-09-16
    Presentation of work at congresses

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  • Automatic keyframe selection based on mutual reinforcement algorithm

     Ventura Royo, Carles; Giro Nieto, Xavier; Vilaplana Besler, Veronica; farre Giribet, Daniel; Carasusan, Eusebio
    International Workshop on Content-Based Multimedia Indexing
    Presentation's date: 2013-06
    Presentation of work at congresses

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    This paper addresses the problem of video summarization through an automatic selection of a single representative keyframe. The proposed solution is based on the mutual reinforcement paradigm, where a keyframe is selected thanks to its highest and most frequent similarity to the rest of considered frames. Two variations of the algorithm are explored: a first one where only frames within the same video are used (intra-clip mode) and a second one where the decision also depends on the previously selected keyframes of related videos (inter-clip mode). These two algorithms were evaluated by a set of professional documentalists from a broadcaster's archive, and results concluded that the proposed techniques outperform the semi-manual solution adopted so far in the company.

    This paper addresses the problem of video summarization through an automatic selection of a single representative keyframe. The proposed solution is based on the mutual reinforcement paradigm, where a keyframe is selected thanks to its highest and most frequent similarity to the rest of considered frames. Two variations of the algorithm are explored: a first one where only frames within the same video are used (intraclip mode) and a second one where the decision also depends on the previously selected keyframes of related videos (interclip mode). These two algorithms were evaluated by a set of professional documentalists from a broadcaster’s archive, and results concluded that the proposed techniques outperform the semi-manual solution adopted so far in the company.

  • Region-based caption text extraction

     León Cristobal, Miriam del Camen; Vilaplana Besler, Veronica; Gasull Llampallas, Antoni; Marques Acosta, Fernando
    Lecture Notes in Electrical Engineering
    Date of publication: 2013
    Journal article

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  • Hierarchical navigation and visual search for video keyframe retrieval

     Ventura Royo, Carles; Martos Asensio, Manuel; Giro Nieto, Xavier; Vilaplana Besler, Veronica; Marques Acosta, Fernando
    International Conference on MultiMedia Modeling
    Presentation's date: 2012-01-06
    Presentation of work at congresses

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  • Video Browser Showdown

     Ventura Royo, Carles; Martos Asensio, Manel; Giro Nieto, Xavier; Vilaplana Besler, Veronica; Marques Acosta, Fernando
    Award or recognition

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  • Algoritmos de anotación e indexado de vídeo: reconocimiento de caras y reconocimiento de texto

     Vilaplana Besler, Veronica; Morros Rubió, Josep Ramon
    Date: 2012-12-31
    Report

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  • Fusión de la anotación multimedia: análisis de cromos y selección de keyframe representativos.

     Vilaplana Besler, Veronica; Morros Rubió, Josep Ramon; Ventura Royo, Carles
    Date: 2012-12-31
    Report

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  • Procesado de vídeo multicámara empleando información de la escena: aplicación a eventos deportivos, interacción visual y 3DTV

     Giro Nieto, Xavier; Oliveras Verges, Albert; Gasull Llampallas, Antoni; Salembier Clairon, Philippe Jean; Marques Acosta, Fernando; Sayrol Clols, Elisa; Pardas Feliu, Montserrat; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier; Vilaplana Besler, Veronica; Casas Pla, Josep Ramon
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  • Algoritmos de anotación e indexado de vídeo, segunda versión

     Vilaplana Besler, Veronica; Morros Rubió, Josep Ramon; Ventura Royo, Carles; Iturraspe, Urtza; Alvarez, Federico; Garcia Serrano, Ana
    Date: 2011-12-30
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  • Fusión de la anotación multimedia

     Alvarez, Federico; Garcia Serrano, Ana; Iturraspe, Urtza; Vilaplana Besler, Veronica; Morros Rubió, Josep Ramon; Loscos, Alex
    Date: 2011-12-31
    Report

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    Object detection and segmentation on a hierarchical region-based image representation  Open access

     Vilaplana Besler, Veronica; Marques Acosta, Fernando; León Cristóbal, Miriam; Gasull Llampallas, Antoni
    IEEE International Conference on Image Processing
    Presentation of work at congresses

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    In this paper we present a general framework for object detection and segmentation. Using a bottom-up unsupervised merging algorithm, a region-based hierarchy that represents the image at different resolution levels is created. Next, top-down, object class knowledge is used to select and combine regions from the hierarchy, in order to define the exact object shape. We illustrate the usefulness of the approach with four different object classes: sky, caption text, traffic signs and faces.

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    Region-based caption text extraction  Open access

     León Cristóbal, Miriam; Vilaplana Besler, Veronica; Gasull Llampallas, Antoni; Marques Acosta, Fernando
    International Workshop on Image Analysis for Multimedia Application Services
    Presentation's date: 2010-04-12
    Presentation of work at congresses

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    This paper presents a method for caption text detection. The proposed method will be included in a generic indexing system dealing with other semantic concepts which are to be automatically detected as well. To have a coherent detection system, the various object detection algorithms use a common image description. In our framework, the image description is a hierarchical region-based image model. The proposed method takes advantage of texture and geometric features to detect the caption text. Texture features are estimated using wavelet analysis and mainly applied for Text candidate spotting. In turn, Text characteristics verification is basically carry out relying on geometric features, which are estimated exploiting the region-based image model. Analysis of the region hierarchy provides the final caption text objects. The final step of Consistency analysis for output is performed by a binarization algorithm that robustly estimates the thresholds on the caption text area of support.

  • Region-based face detection, segmentation and tracking. Framework definition and application to other objects  Open access

     Vilaplana Besler, Veronica
    Defense's date: 2010-12-17
    Department of Signal Theory and Communications, Universitat Politècnica de Catalunya
    Theses

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    One of the central problems in computer vision is the automatic recognition of object classes. In particular, the detection of the class of human faces is a problem that generates special interest due to the large number of applications that require face detection as a first step. In this thesis we approach the problem of face detection as a joint detection and segmentation problem, in order to precisely localize faces with pixel accurate masks. Even though this is our primary goal, in finding a solution we have tried to create a general framework as independent as possible of the type of object being searched. For that purpose, the technique relies on a hierarchical region-based image model, the Binary Partition Tree, where objects are obtained by the union of regions in an image partition. In this work, this model is optimized for the face detection and segmentation tasks. Different merging and stopping criteria are proposed and compared through a large set of experiments. In the proposed system the intra-class variability of faces is managed within a learning framework. The face class is characterized using a set of descriptors measured on the tree nodes, and a set of one-class classifiers. The system is formed by two strong classifiers. First, a cascade of binary classifiers simplifies the search space, and afterwards, an ensemble of more complex classifiers performs the final classification of the tree nodes. The system is extensively tested on different face data sets, producing accurate segmentations and proving to be quite robust to variations in scale, position, orientation, lighting conditions and background complexity. We show that the technique proposed for faces can be easily adapted to detect other object classes. Since the construction of the image model does not depend on any object class, different objects can be detected and segmented using the appropriate object model on the same image model. New object models can be easily built by selecting and training a suitable set of descriptors and classifiers. Finally, a tracking mechanism is proposed. It combines the efficiency of the mean-shift algorithm with the use of regions to track and segment faces through a video sequence, where both the face and the camera may move. The method is extended to deal with other deformable objects, using a region-based graph-cut method for the final object segmentation at each frame. Experiments show that both mean-shift based trackers produce accurate segmentations even in difficult scenarios such as those with similar object and background colors and fast camera and object movements. Lloc i

    Un dels problemes més importants en l'àrea de visió artificial és el reconeixement automàtic de classes d'objectes. En particular, la detecció de la classe de cares humanes és un problema que genera especial interès degut al gran nombre d'aplicacions que requereixen com a primer pas detectar les cares a l'escena. A aquesta tesis s'analitza el problema de detecció de cares com un problema conjunt de detecció i segmentació, per tal de localitzar de manera precisa les cares a l'escena amb màscares que arribin a precisions d'un píxel. Malgrat l'objectiu principal de la tesi és aquest, en el procés de trobar una solució s'ha intentat crear un marc de treball general i tan independent com fos possible del tipus d'objecte que s'està buscant. Amb aquest propòsit, la tècnica proposada fa ús d'un model jeràrquic d'imatge basat en regions, l'arbre binari de particions (BPT: Binary Partition Tree), en el qual els objectes s'obtenen com a unió de regions que provenen d'una partició de la imatge. En aquest treball, s'ha optimitzat el model per a les tasques de detecció i segmentació de cares. Per això, es proposen diferents criteris de fusió i de parada, els quals es comparen en un conjunt ampli d'experiments. En el sistema proposat, la variabilitat dins de la classe cara s'estudia dins d'un marc de treball d'aprenentatge automàtic. La classe cara es caracteritza fent servir un conjunt de descriptors, que es mesuren en els nodes de l'arbre, així com un conjunt de classificadors d'una única classe. El sistema està format per dos classificadors forts. Primer s'utilitza una cascada de classificadors binaris que realitzen una simplificació de l'espai de cerca i, posteriorment, s'aplica un conjunt de classificadors més complexes que produeixen la classificació final dels nodes de l'arbre. El sistema es testeja de manera exhaustiva sobre diferents bases de dades de cares, sobre les quals s'obtenen segmentacions precises provant així la robustesa del sistema en front a variacions d'escala, posició, orientació, condicions d'il·luminació i complexitat del fons de l'escena. A aquesta tesi es mostra també que la tècnica proposada per cares pot ser fàcilment adaptable a la detecció i segmentació d'altres classes d'objectes. Donat que la construcció del model d'imatge no depèn de la classe d'objecte que es pretén buscar, es pot detectar i segmentar diferents classes d'objectes fent servir, sobre el mateix model d'imatge, el model d'objecte apropiat. Nous models d'objecte poden ser fàcilment construïts mitjançant la selecció i l'entrenament d'un conjunt adient de descriptors i classificadors. Finalment, es proposa un mecanisme de seguiment. Aquest mecanisme combina l'eficiència de l'algorisme mean-shift amb l'ús de regions per fer el seguiment i segmentar les cares al llarg d'una seqüència de vídeo a la qual tant la càmera com la cara es poden moure. Aquest mètode s'estén al cas de seguiment d'altres objectes deformables, utilitzant una versió basada en regions de la tècnica de graph-cut per obtenir la segmentació final de l'objecte a cada imatge. Els experiments realitzats mostren que les dues versions del sistema de seguiment basat en l'algorisme mean-shift produeixen segmentacions acurades, fins i tot en entorns complicats com ara quan l'objecte i el fons de l'escena presenten colors similars o quan es produeix un moviment ràpid, ja sigui de la càmera o de l'objecte.

  • Adquisición multicámara para Free Viewpoint Video (MC4FVV)

     Pardas Feliu, Montserrat; Giro Nieto, Xavier; Vilaplana Besler, Veronica; Ruiz Hidalgo, Javier; Morros Rubió, Josep Ramon; Salembier Clairon, Philippe Jean; Marques Acosta, Fernando; Gasull Llampallas, Antoni; Oliveras Verges, Albert; Sayrol Clols, Elisa; Casas Pla, Josep Ramon
    Participation in a competitive project

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  • Activo experimental sobre algoritmos de detección de objetos

     Gasull Llampallas, Antoni; Giro Nieto, Xavier; León Cristóbal, Miriam; López Bakerkina, Khristina; Tapaswi, Makarand; Varas, David; Vilaplana Besler, Veronica; Marques Acosta, Fernando
    Date: 2010-11-28
    Report

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  • Access to the full text
    Face tracking using a region-based mean-shift algorithm with adaptive object and background models  Open access

     Vilaplana Besler, Veronica; Varas, David
    Workshop on Image Analysis for Multimedia Interactive Services
    Presentation's date: 2009-05-06
    Presentation of work at congresses

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    This paper proposes a technique for face tracking based on the mean shift algorithm and the segmentation of the images into regions homogeneous in color. Object and background are explicitly modeled and updated through the tracking process. Color and shape information are used to define with precision the face contours, providing a mechanism to adapt the tracker to variations in object scale and to illumination and background changes.

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    Caption text extraction for indexing purposes using a hierarchical region-based image model  Open access

     León Cristóbal, Miriam; Vilaplana Besler, Veronica; Gasull Llampallas, Antoni; Marques Acosta, Fernando
    IEEE International Conference on Image Processing
    Presentation's date: 2009-11
    Presentation of work at congresses

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    This paper presents a technique for detecting caption text for indexing purposes. This technique is to be included in a generic indexing system dealing with other semantic concepts. The various object detection algorithms are required to share a common image description which, in our case, is a hierarchical region-based image model. Caption text objects are detected combining texture and geometric features, which are estimated using wavelet analysis and taking advantage of the region-based image model, respectively. Analysis of the region hierarchy provides the final caption text objects.

  • Image and video processing tools for HCI

     Canton Ferrer, Cristian; Pardas Feliu, Montserrat; Vilaplana Besler, Veronica
    Date of publication: 2009
    Book chapter

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  • Processament puntual

     Vilaplana Besler, Veronica
    Date of publication: 2009
    Book chapter

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  • Compressió d'imatges

     Vilaplana Besler, Veronica
    Date of publication: 2009
    Book chapter

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  • GRUP DE PROECESSAMENT D'IMATGE I VIDEO (GPI)

     Ruiz Hidalgo, Javier; Marques Acosta, Fernando; Oliveras Verges, Albert; Sayrol Clols, Elisa; Pardas Feliu, Montserrat; Morros Rubió, Josep Ramon; Vilaplana Besler, Veronica; Giro Nieto, Xavier; Gasull Llampallas, Antoni; Salembier Clairon, Philippe Jean; Casas Pla, Josep Ramon
    Participation in a competitive project

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  • Region-based mean shift tracking: Application to face tracking

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    IEEE International Conference on Image Processing
    Presentation of work at congresses

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  • Face and speech interaction

     Vilaplana Besler, Veronica; Marques Acosta, Fernando; Gurban, M; Thiran, J-P
    Date of publication: 2008-10-31
    Book chapter

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  • Desarrollo de los primeros algoritmos de indexación

     Calderero, Felipe; Casas Pla, Josep Ramon; Gasull Llampallas, Antoni; Giro Nieto, Xavier; Miriam, Leon; Marques Acosta, Fernando; Pardas Feliu, Montserrat; Jordi, Pont; Salembier Clairon, Philippe Jean; Vilaplana Besler, Veronica; Morros Rubió, Josep Ramon
    Date: 2008-12
    Report

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  • Binary partition trees for object detection

     Vilaplana Besler, Veronica; Marques Acosta, Fernando; Salembier Clairon, Philippe Jean
    IEEE transactions on image processing
    Date of publication: 2008-11
    Journal article

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  • On building a hierarchical region-based representation for generic image analysis

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    IEEE International Conference on Image Processing
    Presentation of work at congresses

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  • Procesado de vídeo en entornos controlados: aplicación a seguridad, salas inteligentes y telepresencia (PROVEC)

     Casas Pla, Josep Ramon; Gasull Llampallas, Antoni; Giro Nieto, Xavier; Marques Acosta, Fernando; Morros Rubió, Josep Ramon; Oliveras Verges, Albert; Pardas Feliu, Montserrat; Ruiz Hidalgo, Javier; Salembier Clairon, Philippe Jean; Sayrol Clols, Elisa; Vilaplana Besler, Veronica
    Participation in a competitive project

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  • Face detection and segmentation on a hierarchical image representation

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    European Signal Processing Conference
    Presentation of work at congresses

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  • Region-based hierarchical representation for object detection

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    Fith International Workshop on Content-Based Multimedia Indexing
    Presentation of work at congresses

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  • Audio, Video and Multimodal Person Identification in a Smart Room

     Luque, J; Morros Rubió, Josep Ramon; Garde, A; Anguita Ortega, Jan; Farrús Cabecerán, Mireia; Macho, D; Marques Acosta, Fernando; Martínez, C; Vilaplana Besler, Veronica; Hernando Pericas, Francisco Javier
    Lecture notes in computer science
    Date of publication: 2006-01
    Journal article

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  • Multimodal Person Identification in a Smart Room

     Luque, J; Morros Rubió, Josep Ramon; Anguita, J; Farrús, M; Macho, D; Marques Acosta, Fernando; Martínez, C; Vilaplana Besler, Veronica; Hernando Pericas, Francisco Javier
    Jornadas en Tecnología del Habla
    Presentation of work at congresses

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  • Estado del arte de las tecnologías de conocimiento, visión y audio cognitivo

     Ruiz Hidalgo, Javier; Pardas Feliu, Montserrat; Casas Pla, Josep Ramon; Canton Ferrer, Cristian; Ferran Bennström, Igorchristian; Marques Acosta, Fernando; Morros Rubió, Josep Ramon; Vilaplana Besler, Veronica; Giro Nieto, Xavier
    Date: 2006-11
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  • Face Recognition Using Groups of Images in Smart Room Scenarios

     Vilaplana Besler, Veronica; MARTINEZ, CLAUDI; Javier, Cruz; Marques Acosta, Fernando
    IEEE International Conference on Image Processing
    Presentation of work at congresses

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  • Face Recognition Using Groups of Images in Smart Room Scenarios

     Vilaplana Besler, Veronica
    IEEE International Conference on Image Processing
    Presentation's date: 2006-10-08
    Presentation of work at congresses

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  • Audio, Video and Multimodal Person Identification in a Smart Room

     Luque, J; Morros Rubió, Josep Ramon; Garde, A; Anguita Ortega, Jan; Farrús Cabecerán, Mireia; Macho, D; Marques Acosta, Fernando; Martínez, C; Vilaplana Besler, Veronica; Hernando Pericas, Francisco Javier
    CLEAR'06 Evaluation Campaign and Workshop - Classification of Events, Activities and Relationships
    Presentation of work at congresses

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  • Automatic extraction and analysis of visual objects information

     Giro Nieto, Xavier; Vilaplana Besler, Veronica; Marques Acosta, Fernando; Salembier Clairon, Philippe Jean
    Date of publication: 2005-05-31
    Book chapter

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  • 2005SGR-00341 GRUP DE PROCESSAMENT D'IMATGE I VIDEO

     Gasull Llampallas, Antoni; Casas Pla, Josep Ramon; Giro Nieto, Xavier; Marques Acosta, Fernando; Morros Rubió, Josep Ramon; Oliveras Verges, Albert; Pardas Feliu, Montserrat; Ruiz Hidalgo, Javier; Salembier Clairon, Philippe Jean; Sayrol Clols, Elisa; Vilaplana Besler, Veronica
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  • Evaluation Packages for the First CHIL Evaluation Campaign

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    Date: 2005-02
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  • Region-based extraction and analysis of visual objects information

     Vilaplana Besler, Veronica; Giro Nieto, Xavier; Salembier Clairon, Philippe Jean; Marques Acosta, Fernando
    Fourth International Workshop on Content-Based Multimedia Indexing
    Presentation of work at congresses

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  • Support Vector Data Description Based on PCA Features for Face Detection

     Vilaplana Besler, Veronica
    European Signal Processing Conference
    Presentation's date: 2005-09-04
    Presentation of work at congresses

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  • Support Vector Data Description Based on PCA Features for Face Detection

     Vilaplana Besler, Veronica; Marques Acosta, Fernando
    European Signal Processing Conference
    Presentation of work at congresses

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  • Las Mancomunidades en España

     Figueras, P Riera; Haas, C; Capdevila, C Amer; Vilaplana Besler, Veronica
    Boletin de la Asociacion de Geografos Espa¿oles
    Date of publication: 2005-06
    Journal article

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  • Report on Multimodal Análisis and Synthesis (M6)

     Marques Acosta, Fernando; Vilaplana Besler, Veronica
    Date: 2004-07
    Report

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  • Robust Tracking of Hands and Faces

     Marques Acosta, Fernando; Vilaplana Besler, Veronica
    Date: 2004-09
    Report

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  • Report on Multimodal Análisis and Synthesis (M12)

     Marques Acosta, Fernando; Vilaplana Besler, Veronica
    Date: 2004-12
    Report

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  • Object recognition based on Binary Partition Trees

     Salerno, O; Pardas Feliu, Montserrat; Vilaplana Besler, Veronica; Marques Acosta, Fernando
    IEEE International Conference on Image Processing
    Presentation of work at congresses

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  • IEEE transactions on image processing

     Vilaplana Besler, Veronica
    Collaboration in journals

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  • Face segmentation and tracking based on connected operators and partition projection

     Marques Acosta, Fernando; Vilaplana Besler, Veronica
    Pattern recognition
    Date of publication: 2002-01
    Journal article

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