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Author M.Gomez; J.Mauri; E.Fernandez-Nofrerias; O.Rodriguez-Leor; C.Julia; Oriol Pujol; Petia Radeva edit  openurl
  Title Diferenciacion de las estructuras del vaso coronario mediante el procesamiento de imagenes y el analisis de las diferentes texturas a partir de la ecografia intracoronaria Type Journal
  Year 2002 Publication (down) XXXVIII Congreso Nacional de la Sociedad Española de Cardiologia Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Madrid  
  Corporate Author 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 MILAB;HuPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ GMF2002f Serial 433  
Permanent link to this record
 

 
Author Simone Balocco; Carlo Gatta; Oriol Pujol; J. Mauri; Petia Radeva edit  doi
openurl 
  Title SRBF: Speckle Reducing Bilateral Filtering Type Journal Article
  Year 2010 Publication (down) Ultrasound in Medicine and Biology Abbreviated Journal UMB  
  Volume 36 Issue 8 Pages 1353-1363  
  Keywords  
  Abstract Speckle noise negatively affects medical ultrasound image shape interpretation and boundary detection. Speckle removal filters are widely used to selectively remove speckle noise without destroying important image features to enhance object boundaries. In this article, a fully automatic bilateral filter tailored to ultrasound images is proposed. The edge preservation property is obtained by embedding noise statistics in the filter framework. Consequently, the filter is able to tackle the multiplicative behavior modulating the smoothing strength with respect to local statistics. The in silico experiments clearly showed that the speckle reducing bilateral filter (SRBF) has superior performances to most of the state of the art filtering methods. The filter is tested on 50 in vivo US images and its influence on a segmentation task is quantified. The results using SRBF filtered data sets show a superior performance to using oriented anisotropic diffusion filtered images. This improvement is due to the adaptive support of SRBF and the embedded noise statistics, yielding a more homogeneous smoothing. SRBF results in a fully automatic, fast and flexible algorithm potentially suitable in wide ranges of speckle noise sizes, for different medical applications (IVUS, B-mode, 3-D matrix array US).  
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  Series Volume Series Issue Edition  
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  Area Expedition Conference  
  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ BGP2010 Serial 1314  
Permanent link to this record
 

 
Author Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu edit   pdf
doi  openurl
  Title Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction Type Journal Article
  Year 2012 Publication (down) Sensors Abbreviated Journal SENS  
  Volume 12 Issue 2 Pages 1702-1719  
  Keywords  
  Abstract IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
 
  Address  
  Corporate Author Thesis  
  Publisher Molecular Diversity Preservation International Place of Publication Editor  
  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ EBV2012 Serial 1885  
Permanent link to this record
 

 
Author Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera edit   pdf
doi  openurl
  Title GrabCut-Based Human Segmentation in Video Sequences Type Journal Article
  Year 2012 Publication (down) Sensors Abbreviated Journal SENS  
  Volume 12 Issue 11 Pages 15376-15393  
  Keywords segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field  
  Abstract In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology.  
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  Language Summary Language Original Title  
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  Area Expedition Conference  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ HRP2012 Serial 2147  
Permanent link to this record
 

 
Author Xavier Perez Sala; Sergio Escalera; Cecilio Angulo; Jordi Gonzalez edit   pdf
doi  openurl
  Title A survey on model based approaches for 2D and 3D visual human pose recovery Type Journal Article
  Year 2014 Publication (down) Sensors Abbreviated Journal SENS  
  Volume 14 Issue 3 Pages 4189-4210  
  Keywords human pose recovery; human body modelling; behavior analysis; computer vision  
  Abstract Human Pose Recovery has been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a general taxonomy to group model based approaches for Human Pose Recovery, which is composed of five main modules: appearance, viewpoint, spatial relations, temporal consistence, and behavior. Subsequently, a methodological comparison is performed following the proposed taxonomy, evaluating current SoA approaches in the aforementioned five group categories. As a result of this comparison, we discuss the main advantages and drawbacks of the reviewed literature.  
  Address  
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  Publisher Place of Publication Editor  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HuPBA; ISE; 600.046; 600.063; 600.078;MILAB Approved no  
  Call Number Admin @ si @ PEA2014 Serial 2443  
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