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Author Hugo Berti; Angel Sappa; Osvaldo Agamennoni edit  openurl
  Title Improved Dynamic Window Approach by Using Lyapunov Stability Criteria Type Journal
  Year 2008 Publication (up) Latin American Applied Research Abbreviated Journal  
  Volume 38 Issue 4 Pages 289–298  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ BSA2008 Serial 1056  
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Author Fadi Dornaika; Angel Sappa edit  openurl
  Title Evaluation of an Appearance-based 3D Face Tracker using Dense 3D Data Type Journal
  Year 2008 Publication (up) Machine Vision and Applications Abbreviated Journal  
  Volume 19 Issue 5-6 Pages 427–441  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ DoS2008b Serial 1018  
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Author Joan Serrat; Felipe Lumbreras; Idoia Ruiz edit  url
openurl 
  Title Learning to measure for preshipment garment sizing Type Journal Article
  Year 2018 Publication (up) Measurement Abbreviated Journal MEASURE  
  Volume 130 Issue Pages 327-339  
  Keywords Apparel; Computer vision; Structured prediction; Regression  
  Abstract Clothing is still manually manufactured for the most part nowadays, resulting in discrepancies between nominal and real dimensions, and potentially ill-fitting garments. Hence, it is common in the apparel industry to manually perform measures at preshipment time. We present an automatic method to obtain such measures from a single image of a garment that speeds up this task. It is generic and extensible in the sense that it does not depend explicitly on the garment shape or type. Instead, it learns through a probabilistic graphical model to identify the different contour parts. Subsequently, a set of Lasso regressors, one per desired measure, can predict the actual values of the measures. We present results on a dataset of 130 images of jackets and 98 of pants, of varying sizes and styles, obtaining 1.17 and 1.22 cm of mean absolute error, respectively.  
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  Notes ADAS: MSIAU; 600.122; 600.118 Approved no  
  Call Number Admin @ si @ SLR2018 Serial 3128  
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Author Naveen Onkarappa; Angel Sappa edit  doi
openurl 
  Title Synthetic sequences and ground-truth flow field generation for algorithm validation Type Journal Article
  Year 2015 Publication (up) Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 74 Issue 9 Pages 3121-3135  
  Keywords Ground-truth optical flow; Synthetic sequence; Algorithm validation  
  Abstract Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems.  
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  Publisher Springer US Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1380-7501 ISBN Medium  
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  Notes ADAS; 600.055; 601.215; 600.076 Approved no  
  Call Number Admin @ si @ OnS2014b Serial 2472  
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Author Marçal Rusiñol; J. Chazalon; Katerine Diaz edit   pdf
doi  openurl
  Title Augmented Songbook: an Augmented Reality Educational Application for Raising Music Awareness Type Journal Article
  Year 2018 Publication (up) Multimedia Tools and Applications Abbreviated Journal MTAP  
  Volume 77 Issue 11 Pages 13773-13798  
  Keywords Augmented reality; Document image matching; Educational applications  
  Abstract This paper presents the development of an Augmented Reality mobile application which aims at sensibilizing young children to abstract concepts of music. Such concepts are, for instance, the musical notation or the idea of rhythm. Recent studies in Augmented Reality for education suggest that such technologies have multiple benefits for students, including younger ones. As mobile document image acquisition and processing gains maturity on mobile platforms, we explore how it is possible to build a markerless and real-time application to augment the physical documents with didactic animations and interactive virtual content. Given a standard image processing pipeline, we compare the performance of different local descriptors at two key stages of the process. Results suggest alternatives to the SIFT local descriptors, regarding result quality and computational efficiency, both for document model identification and perspective transform estimation. All experiments are performed on an original and public dataset we introduce here.  
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  Notes DAG; ADAS; 600.084; 600.121; 600.118 Approved no  
  Call Number Admin @ si @ RCD2018 Serial 2996  
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Author Monica Piñol; Angel Sappa; Ricardo Toledo edit  doi
openurl 
  Title Adaptive Feature Descriptor Selection based on a Multi-Table Reinforcement Learning Strategy Type Journal Article
  Year 2015 Publication (up) Neurocomputing Abbreviated Journal NEUCOM  
  Volume 150 Issue A Pages 106–115  
  Keywords Reinforcement learning; Q-learning; Bag of features; Descriptors  
  Abstract This paper presents and evaluates a framework to improve the performance of visual object classification methods, which are based on the usage of image feature descriptors as inputs. The goal of the proposed framework is to learn the best descriptor for each image in a given database. This goal is reached by means of a reinforcement learning process using the minimum information. The visual classification system used to demonstrate the proposed framework is based on a bag of features scheme, and the reinforcement learning technique is implemented through the Q-learning approach. The behavior of the reinforcement learning with different state definitions is evaluated. Additionally, a method that combines all these states is formulated in order to select the optimal state. Finally, the chosen actions are obtained from the best set of image descriptors in the literature: PHOW, SIFT, C-SIFT, SURF and Spin. Experimental results using two public databases (ETH and COIL) are provided showing both the validity of the proposed approach and comparisons with state of the art. In all the cases the best results are obtained with the proposed approach.  
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  Notes ADAS; 600.055; 600.076 Approved no  
  Call Number Admin @ si @ PST2015 Serial 2473  
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Author J. Pladellorens; M.J. Yzuel; J. Castell; Joan Serrat edit  openurl
  Title Calculo automatico del volumen del ventriculo izquierdo. Comparacion con expertos. Type Journal
  Year 1993 Publication (up) Optica Pura y Aplicada. Abbreviated Journal  
  Volume 26 Issue 3 Pages 685–691  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PYC1993 Serial 149  
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Author Daniel Ponsa; Robert Benavente; Felipe Lumbreras; J. Martinez; Xavier Roca edit  openurl
  Title Quality control of safety belts by machine vision inspection for real-time production Type Journal
  Year 2003 Publication (up) Optical Engineering, 42:1114–1120 (IF: 0.877) Abbreviated Journal  
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  Notes ADAS;ISE;CIC Approved no  
  Call Number ADAS @ adas @ PRL2003 Serial 399  
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Author Daniel Ponsa; Antonio Lopez edit   pdf
doi  openurl
  Title Variance reduction techniques in particle-based visual contour Tracking Type Journal Article
  Year 2009 Publication (up) Pattern Recognition Abbreviated Journal PR  
  Volume 42 Issue 11 Pages 2372–2391  
  Keywords Contour tracking; Active shape models; Kalman filter; Particle filter; Importance sampling; Unscented particle filter; Rao-Blackwellization; Partitioned sampling  
  Abstract This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done.  
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  Notes ADAS Approved no  
  Call Number ADAS @ adas @ PoL2009a Serial 1168  
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Author Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta edit   pdf
doi  openurl
  Title Structure-preserving smoothing of biomedical images Type Journal Article
  Year 2011 Publication (up) Pattern Recognition Abbreviated Journal PR  
  Volume 44 Issue 9 Pages 1842-1851  
  Keywords Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography  
  Abstract Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.  
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  ISSN 0031-3203 ISBN Medium  
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  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ GHB2011 Serial 1526  
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