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Author Egils Avots; Meysam Madadi; Sergio Escalera; Jordi Gonzalez; Xavier Baro; Paul Pallin; Gholamreza Anbarjafari edit   pdf
url  doi
openurl 
  Title From 2D to 3D geodesic-based garment matching Type Journal Article
  Year 2019 Publication Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 78 Issue 18 Pages 25829–25853  
  Keywords Shape matching; Geodesic distance; Texture mapping; RGBD image processing; Gaussian mixture model  
  Abstract (up) A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS). An automatically segmented garment of an individual is matched to a new source garment and rendered, resulting in augmented images in which the target garment has been retextured using the texture of the source garment. We divide the problem into garment boundary matching based on Gaussian mixture models and then interpolate inner points using surface topology extracted through geodesic paths, which leads to a more realistic result than standard approaches. We evaluated and compared our system quantitatively by root mean square error (RMS) and qualitatively using the mean opinion score (MOS), showing the benefits of the proposed methodology on our gathered dataset.  
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  Notes HuPBA; ISE; 600.098; 600.119; 602.133;MV;OR;MILAB Approved no  
  Call Number Admin @ si @ AME2019 Serial 3317  
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Author Andres Traumann; Gholamreza Anbarjafari; Sergio Escalera edit  doi
openurl 
  Title Accurate 3D Measurement Using Optical Depth Information Type Journal Article
  Year 2015 Publication Electronic Letters Abbreviated Journal EL  
  Volume 51 Issue 18 Pages 1420-1422  
  Keywords  
  Abstract (up) A novel three-dimensional measurement technique is proposed. The methodology consists in mapping from the screen coordinates reported by the optical camera to the real world, and integrating distance gradients from the beginning to the end point, while also minimising the error through fitting pixel locations to a smooth curve. The results demonstrate accuracy of less than half a centimetre using Microsoft Kinect II.  
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  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ TAE2015 Serial 2647  
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Author Sergio Escalera; Oriol Pujol; Petia Radeva edit  url
doi  openurl
  Title Re-coding ECOCs without retraining Type Journal Article
  Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 31 Issue 7 Pages 555–562  
  Keywords  
  Abstract (up) A standard way to deal with multi-class categorization problems is by the combination of binary classifiers in a pairwise voting procedure. Recently, this classical approach has been formalized in the Error-Correcting Output Codes (ECOC) framework. In the ECOC framework, the one-versus-one coding demonstrates to achieve higher performance than the rest of coding designs. The binary problems that we train in the one-versus-one strategy are significantly smaller than in the rest of designs, and usually easier to be learnt, taking into account the smaller overlapping between classes. However, a high percentage of the positions coded by zero of the coding matrix, which implies a high sparseness degree, does not codify meta-class membership information. In this paper, we show that using the training data we can redefine without re-training, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information helps the system to increase its generalization capability. Moreover, the new re-coding strategy is generalized to be applied over any binary code. The results over several UCI Machine Learning repository data sets and two real multi-class problems show that performance improvements can be obtained re-coding the classical one-versus-one and Sparse random designs compared to different state-of-the-art ECOC configurations.  
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  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
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  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ EPR2010e Serial 1338  
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Author Francesco Ciompi; Oriol Pujol; Carlo Gatta; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva edit  url
doi  openurl
  Title Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization Type Journal Article
  Year 2010 Publication International Journal of Cardiovascular Imaging Abbreviated Journal IJCI  
  Volume 26 Issue 7 Pages 763–779  
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  Abstract (up) Accurate detection of in-vivo vulnerable plaque in coronary arteries is still an open problem. Recent studies show that it is highly related to tissue structure and composition. Intravascular Ultrasound (IVUS) is a powerful imaging technique that gives a detailed cross-sectional image of the vessel, allowing to explore arteries morphology. IVUS data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue. The main drawback of this method is the few number of available case studies and validated data due to the complex procedure of histological analysis of the tissue. On the other hand, IVUS data from in-vivo cases is easy to obtain but it can not be histologically validated. In this work, we propose to enhance the in-vitro training data set by selectively including examples from in-vivo plaques. For this purpose, a Sequential Floating Forward Selection method is reformulated in the context of plaque characterization. The enhanced classifier performance is validated on in-vitro data set, yielding an overall accuracy of 91.59% in discriminating among fibrotic, lipidic and calcified plaques, while reducing the gap between in-vivo and in-vitro data analysis. Experimental results suggest that the obtained classifier could be properly applied on in-vivo plaque characterization and also demonstrate that the common hypothesis of assuming the difference between in-vivo and in-vitro as negligible is incorrect.  
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  ISSN 1569-5794 ISBN Medium  
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  Notes MILAB;HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ CPG2010 Serial 1305  
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Author David Rotger; Misael Rosales; Jaume Garcia; Oriol Pujol ; J. Mauri; Petia Radeva edit   pdf
doi  openurl
  Title Active Vessel: A New Multimedia Workstation for Intravascular Ultrasound and Angiography Fusion Type Journal Article
  Year 2003 Publication Computers in Cardiology Abbreviated Journal  
  Volume 30 Issue Pages 65-68  
  Keywords  
  Abstract (up) AcriveVessel is a new multimedia workstation which enables the visualization, acquisition and handling of both image modalities, on- and ofline. It enables DICOM v3.0 decompression and browsing, video acquisition,repmduction and storage for IntraVascular UltraSound (IVUS) and angiograms with their corresponding ECG,automatic catheter segmentation in angiography images (using fast marching algorithm). BSpline models definition for vessel layers on IVUS images sequence and an extensively validated tool to fuse information. This approach defines the correspondence of every IVUS image with its correspondent point in the angiogram and viceversa. The 3 0 reconstruction of the NUS catheterhessel enables real distance measurements as well as threedimensional visualization showing vessel tortuosity in the space.  
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  Area Expedition Conference  
  Notes IAM;MILAB;HuPBA Approved no  
  Call Number IAM @ iam @ RRG2003 Serial 1647  
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