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Author (down) Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers edit   pdf
doi  openurl
  Title Like Father, Like Son: Facial Expression Dynamics for Kinship Verification Type Conference Article
  Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 1497-1504  
  Keywords  
  Abstract Kinship verification from facial appearance is a difficult problem. This paper explores the possibility of employing facial expression dynamics in this problem. By using features that describe facial dynamics and spatio-temporal appearance over smile expressions, we show that it is possible to improve the state of the art in this problem, and verify that it is indeed possible to recognize kinship by resemblance of facial expressions. The proposed method is tested on different kin relationships. On the average, 72.89% verification accuracy is achieved on spontaneous smiles.  
  Address Sydney  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference ICCV  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DSG2013 Serial 2366  
Permanent link to this record
 

 
Author (down) Hamdi Dibeklioglu; Albert Ali Salah; Theo Gevers edit  doi
openurl 
  Title A Statistical Method for 2D Facial Landmarking Type Journal Article
  Year 2012 Publication IEEE Transactions on Image Processing Abbreviated Journal TIP  
  Volume 21 Issue 2 Pages 844-858  
  Keywords  
  Abstract IF = 3.32
Many facial-analysis approaches rely on robust and accurate automatic facial landmarking to correctly function. In this paper, we describe a statistical method for automatic facial-landmark localization. Our landmarking relies on a parsimonious mixture model of Gabor wavelet features, computed in coarse-to-fine fashion and complemented with a shape prior. We assess the accuracy and the robustness of the proposed approach in extensive cross-database conditions conducted on four face data sets (Face Recognition Grand Challenge, Cohn-Kanade, Bosphorus, and BioID). Our method has 99.33% accuracy on the Bosphorus database and 97.62% accuracy on the BioID database on the average, which improves the state of the art. We show that the method is not significantly affected by low-resolution images, small rotations, facial expressions, and natural occlusions such as beard and mustache. We further test the goodness of the landmarks in a facial expression recognition application and report landmarking-induced improvement over baseline on two separate databases for video-based expression recognition (Cohn-Kanade and BU-4DFE).
 
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  Series Volume Series Issue Edition  
  ISSN 1057-7149 ISBN Medium  
  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ DSG 2012 Serial 1853  
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Author (down) H.M.G. Stokman; Theo Gevers edit  openurl
  Title Selection and Fusion of Color Models for Image Feature Detection Type Journal
  Year 2007 Publication IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.29(3):371–381 Abbreviated Journal  
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  Area Expedition Conference  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ StG2007 Serial 948  
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Author (down) H. Martin Kjer; Jens Fagertun; Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester; Rasmus R. Paulsena edit   pdf
url  openurl
  Title Free-form image registration of human cochlear uCT data using skeleton similarity as anatomical prior Type Journal Article
  Year 2016 Publication Patter Recognition Letters Abbreviated Journal PRL  
  Volume 76 Issue 1 Pages 76-82  
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  Area Expedition Conference  
  Notes IAM; 600.060 Approved no  
  Call Number Admin @ si @ MFV2017b Serial 2941  
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Author (down) H. Martin Kjer; Jens Fagertun; Sergio Vera; Debora Gil edit   pdf
openurl 
  Title Medial structure generation for registration of anatomical structures Type Book Chapter
  Year 2017 Publication Skeletonization, Theory, Methods and Applications Abbreviated Journal  
  Volume 11 Issue Pages  
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  Area Expedition Conference  
  Notes IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ MFV2017a Serial 2935  
Permanent link to this record
 

 
Author (down) H. Emrah Tasli; Jan van Gemert; Theo Gevers edit  doi
openurl 
  Title Spot the differences: from a photograph burst to the single best picture Type Conference Article
  Year 2013 Publication 21ST ACM International Conference on Multimedia Abbreviated Journal  
  Volume Issue Pages 729-732  
  Keywords  
  Abstract With the rise of the digital camera, people nowadays typically take several near-identical photos of the same scene to maximize the chances of a good shot. This paper proposes a user-friendly tool for exploring a personal photo gallery for selecting or even creating the best shot of a scene between its multiple alternatives. This functionality is realized through a graphical user interface where the best viewpoint can be selected from a generated panorama of the scene. Once the viewpoint is selected, the user is able to go explore possible alternatives coming from the other images. Using this tool, one can explore a photo gallery efficiently. Moreover, additional compositions from other images are also possible. With such additional compositions, one can go from a burst of photographs to the single best one. Even funny compositions of images, where you can duplicate a person in the same image, are possible with our proposed tool.  
  Address Barcelona  
  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 ACM-MM  
  Notes ALTRES;ISE Approved no  
  Call Number TGG2013 Serial 2368  
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Author (down) H. Emrah Tasli; Cevahir Çigla; Theo Gevers; A. Aydin Alatan edit  doi
openurl 
  Title Super pixel extraction via convexity induced boundary adaptation Type Conference Article
  Year 2013 Publication 14th IEEE International Conference on Multimedia and Expo Abbreviated Journal  
  Volume Issue Pages 1-6  
  Keywords  
  Abstract This study presents an efficient super-pixel extraction algorithm with major contributions to the state-of-the-art in terms of accuracy and computational complexity. Segmentation accuracy is improved through convexity constrained geodesic distance utilization; while computational efficiency is achieved by replacing complete region processing with boundary adaptation idea. Starting from the uniformly distributed rectangular equal-sized super-pixels, region boundaries are adapted to intensity edges iteratively by assigning boundary pixels to the most similar neighboring super-pixels. At each iteration, super-pixel regions are updated and hence progressively converging to compact pixel groups. Experimental results with state-of-the-art comparisons, validate the performance of the proposed technique in terms of both accuracy and speed.  
  Address San Jose; USA; July 2013  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN 1945-7871 ISBN Medium  
  Area Expedition Conference ICME  
  Notes ALTRES;ISE Approved no  
  Call Number Admin @ si @ TÇG2013 Serial 2367  
Permanent link to this record
 

 
Author (down) H. Chouaib; Salvatore Tabbone; Oriol Ramos Terrades; F. Cloppet; N. Vincent; A.T. Thierry Paquet edit  openurl
  Title Sélection de Caractéristiques à partir d'un algorithme génétique et d'une combinaison de classifieurs Adaboost Type Conference Article
  Year 2008 Publication Colloque International Francophone sur l'Ecrit et le Document Abbreviated Journal  
  Volume Issue Pages 181-186  
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  Address Rouen, France  
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  ISSN ISBN Medium  
  Area Expedition Conference CIFED  
  Notes DAG Approved no  
  Call Number Admin @ si @ CTR2008 Serial 1874  
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Author (down) H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent edit  doi
openurl 
  Title Feature Selection Combining Genetic Algorithm and Adaboost Classifiers Type Conference Article
  Year 2008 Publication 19th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 1-4  
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  Address Tampa, Florida  
  Corporate Author Thesis  
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  ISSN ISBN Medium  
  Area Expedition Conference ICPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ CRT2008 Serial 1872  
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Author (down) Guim Perarnau; Joost Van de Weijer; Bogdan Raducanu; Jose Manuel Alvarez edit   pdf
openurl 
  Title Invertible conditional gans for image editing Type Conference Article
  Year 2016 Publication 30th Annual Conference on Neural Information Processing Systems Worshops Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Generative Adversarial Networks (GANs) have recently demonstrated to successfully approximate complex data distributions. A relevant extension of this model is conditional GANs (cGANs), where the introduction of external information allows to determine specific representations of the generated images. In this work, we evaluate encoders to inverse the mapping of a cGAN, i.e., mapping a real image into a latent space and a conditional representation. This allows, for example, to reconstruct and modify real images of faces conditioning on arbitrary attributes.
Additionally, we evaluate the design of cGANs. The combination of an encoder
with a cGAN, which we call Invertible cGAN (IcGAN), enables to re-generate real
images with deterministic complex modifications.
 
  Address Barcelona; Spain; December 2016  
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  ISSN ISBN Medium  
  Area Expedition Conference NIPSW  
  Notes LAMP; ADAS; 600.068 Approved no  
  Call Number Admin @ si @ PWR2016 Serial 2906  
Permanent link to this record
 

 
Author (down) Guillermo Torres; Sonia Baeza; Carles Sanchez; Ignasi Guasch; Antoni Rosell; Debora Gil edit  doi
openurl 
  Title An Intelligent Radiomic Approach for Lung Cancer Screening Type Journal Article
  Year 2022 Publication Applied Sciences Abbreviated Journal APPLSCI  
  Volume 12 Issue 3 Pages 1568  
  Keywords Lung cancer; Early diagnosis; Screening; Neural networks; Image embedding; Architecture optimization  
  Abstract The efficiency of lung cancer screening for reducing mortality is hindered by the high rate of false positives. Artificial intelligence applied to radiomics could help to early discard benign cases from the analysis of CT scans. The available amount of data and the fact that benign cases are a minority, constitutes a main challenge for the successful use of state of the art methods (like deep learning), which can be biased, over-fitted and lack of clinical reproducibility. We present an hybrid approach combining the potential of radiomic features to characterize nodules in CT scans and the generalization of the feed forward networks. In order to obtain maximal reproducibility with minimal training data, we propose an embedding of nodules based on the statistical significance of radiomic features for malignancy detection. This representation space of lesions is the input to a feed
forward network, which architecture and hyperparameters are optimized using own-defined metrics of the diagnostic power of the whole system. Results of the best model on an independent set of patients achieve 100% of sensitivity and 83% of specificity (AUC = 0.94) for malignancy detection.
 
  Address Jan 2022  
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  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ TBS2022 Serial 3699  
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Author (down) Guillermo Torres; Jan Rodríguez Dueñas; Sonia Baeza; Antoni Rosell; Carles Sanchez; Debora Gil edit   pdf
url  openurl
  Title Prediction of Malignancy in Lung Cancer using several strategies for the fusion of Multi-Channel Pyradiomics Images Type Conference Article
  Year 2023 Publication 7th Workshop on Digital Image Processing for Medical and Automotive Industry in the framework of SYNASC 2023 Abbreviated Journal  
  Volume Issue Pages  
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  Abstract This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level.  
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  ISSN ISBN Medium  
  Area Expedition Conference DIPMAI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TRB2023 Serial 3926  
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Author (down) Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez edit  openurl
  Title A radiomic biopsy for virtual histology of pulmonary nodules Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
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  Address Cartagena de Indias; Colombia; April 2023  
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  ISSN ISBN Medium  
  Area Expedition Conference ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023b Serial 3954  
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Author (down) Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez edit  openurl
  Title Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules – Intermediate Results of the RadioLung Project Type Journal Article
  Year 2023 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCARS  
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  Notes IAM Approved no  
  Call Number Admin @ si @ TGM2023 Serial 3830  
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Author (down) Guillermo Torres; Debora Gil; Antoni Rosell; S. Mena; Carles Sanchez edit  openurl
  Title Virtual Radiomics Biopsy for the Histological Diagnosis of Pulmonary Nodules Type Conference Article
  Year 2023 Publication 37th International Congress and Exhibition is organized by Computer Assisted Radiology and Surgery Abbreviated Journal  
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  Address Munich; Germany; June 2023  
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  ISSN ISBN Medium  
  Area Expedition Conference CARS  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023a Serial 3950  
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