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Author Giovanni Maria Farinella; Petia Radeva; Jose Braz edit  openurl
  Title Proceedings of the 15th International Joint Conference on Computer Vision; Imaging and Computer Graphics Theory and Applications Type Book Whole
  Year 2020 Publication (down) Proceedings of the 15th International Joint Conference on Computer Vision; Imaging and Computer Graphics Theory and Applications; VISIGRAPP 2020 Abbreviated Journal  
  Volume 4 Issue Pages  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB Approved no  
  Call Number Admin @ si @ FRB2020a Serial 3546  
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Author Giovanni Maria Farinella; Petia Radeva; Jose Braz edit  openurl
  Title Proceedings of the 15th International Joint Conference on Computer Vision; Imaging and Computer Graphics Theory and Applications Type Book Whole
  Year 2020 Publication (down) Proceedings of the 15th International Joint Conference on Computer Vision; Imaging and Computer Graphics Theory and Applications; VISIGRAPP 2020 Abbreviated Journal  
  Volume 5 Issue Pages  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB Approved no  
  Call Number Admin @ si @ FRB2020b Serial 3547  
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Author Josep Llados; Jaime Lopez-Krahe; Enric Marti edit   pdf
doi  openurl
  Title Hand drawn document understanding using the straight line Hough transform and graph matching Type Conference Article
  Year 1996 Publication (down) Proceedings of the 13th International Pattern Recognition Conference (ICPR’96) Abbreviated Journal  
  Volume 2 Issue Pages 497-501  
  Keywords  
  Abstract This paper presents a system to understand hand drawn architectural drawings in a CAD environment. The procedure is to identify in a floor plan the building elements, stored in a library of patterns, and their spatial relationships. The vectorized input document and the patterns to recognize are represented by attributed graphs. To recognize the patterns as such, we apply a structural approach based on subgraph isomorphism techniques. In spite of their value, graph matching techniques do not recognize adequately those building elements characterized by hatching patterns, i.e. walls. Here we focus on the recognition of hatching patterns and develop a straight line Hough transform based method in order to detect the regions filled in with parallel straight fines. This allows not only to recognize filling patterns, but it actually reduces the computational load associated with the subgraph isomorphism computation. The result is that the document can be redrawn by editing all the patterns recognized  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Vienna , Austria 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 DAG;IAM; Approved no  
  Call Number IAM @ iam @ LLM1996 Serial 1579  
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Author Bojana Gajic; Eduard Vazquez; Ramon Baldrich edit  url
openurl 
  Title Evaluation of Deep Image Descriptors for Texture Retrieval Type Conference Article
  Year 2017 Publication (down) Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) Abbreviated Journal  
  Volume Issue Pages 251-257  
  Keywords Texture Representation; Texture Retrieval; Convolutional Neural Networks; Psychophysical Evaluation  
  Abstract The increasing complexity learnt in the layers of a Convolutional Neural Network has proven to be of great help for the task of classification. The topic has received great attention in recently published literature.
Nonetheless, just a handful of works study low-level representations, commonly associated with lower layers. In this paper, we explore recent findings which conclude, counterintuitively, the last layer of the VGG convolutional network is the best to describe a low-level property such as texture. To shed some light on this issue, we are proposing a psychophysical experiment to evaluate the adequacy of different layers of the VGG network for texture retrieval. Results obtained suggest that, whereas the last convolutional layer is a good choice for a specific task of classification, it might not be the best choice as a texture descriptor, showing a very poor performance on texture retrieval. Intermediate layers show the best performance, showing a good combination of basic filters, as in the primary visual cortex, and also a degree of higher level information to describe more complex textures.
 
  Address Porto, Portugal; 27 February – 1 March 2017  
  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 VISIGRAPP  
  Notes CIC; 600.087 Approved no  
  Call Number Admin @ si @ Serial 3710  
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Author Antoni Gurgui; Debora Gil; Enric Marti edit  url
doi  isbn
openurl 
  Title Laplacian Unitary Domain for Texture Morphing Type Conference Article
  Year 2015 Publication (down) Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 Abbreviated Journal  
  Volume 1 Issue Pages 693-699  
  Keywords Facial; metamorphosis;LaplacianMorphing  
  Abstract Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.  
  Address Munich; Germany; February 2015  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-758-089-5 Medium  
  Area Expedition Conference VISAPP  
  Notes IAM; 600.075 Approved no  
  Call Number Admin @ si @ GGM2015 Serial 2614  
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Author Paula Fritzsche; C.Roig; Ana Ripoll; Emilio Luque; Aura Hernandez-Sabate edit   pdf
doi  openurl
  Title A Performance Prediction Methodology for Data-dependent Parallel Applications Type Conference Article
  Year 2006 Publication (down) Proceedings of the IEEE International Conference on Cluster Computing Abbreviated Journal  
  Volume Issue Pages 1-8  
  Keywords  
  Abstract The increase in the use of parallel distributed architectures in order to solve large-scale scientific problems has generated the need for performance prediction for both deterministic applications and non-deterministic applications. In particular, the performance prediction of data dependent programs is an extremely challenging problem because for a specific issue the input datasets may cause different execution times. Generally, a parallel application is characterized as a collection of tasks and their interrelations. If the application is time-critical it is not enough to work with only one value per task, and consequently knowledge of the distribution of task execution times is crucial. The development of a new prediction methodology to estimate the performance of data-dependent parallel applications is the primary target of this study. This approach makes it possible to evaluate the parallel performance of an application without the need of implementation. A real data-dependent arterial structure detection application model is used to apply the methodology proposed. The predicted times obtained using the new methodology for genuine datasets are compared with predicted times that arise from using only one execution value per task. Finally, the experimental study shows that the new methodology generates more precise predictions.  
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  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ FRR2006 Serial 1497  
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Author Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva edit  doi
openurl 
  Title Towards social interaction detection in egocentric photo-streams Type Conference Article
  Year 2015 Publication (down) Proceedings of SPIE, 8th International Conference on Machine Vision , ICMV 2015 Abbreviated Journal  
  Volume 9875 Issue Pages  
  Keywords  
  Abstract Detecting social interaction in videos relying solely on visual cues is a valuable task that is receiving increasing attention in recent years. In this work, we address this problem in the challenging domain of egocentric photo-streams captured by a low temporal resolution wearable camera (2fpm). The major difficulties to be handled in this context are the sparsity of observations as well as unpredictability of camera motion and attention orientation due to the fact that the camera is worn as part of clothing. Our method consists of four steps: multi-faces localization and tracking, 3D localization, pose estimation and analysis of f-formations. By estimating pair-to-pair interaction probabilities over the sequence, our method states the presence or absence of interaction with the camera wearer and specifies which people are more involved in the interaction. We tested our method over a dataset of 18.000 images and we show its reliability on our considered purpose. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.  
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  ISSN ISBN Medium  
  Area Expedition Conference ICMV  
  Notes MILAB Approved no  
  Call Number Admin @ si @ ADR2015a Serial 2702  
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti edit  url
isbn  openurl
  Title A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa Type Conference Article
  Year 2003 Publication (down) Proceedings of Pattern Recognition in Information Systems Abbreviated Journal  
  Volume Issue Pages 1-13  
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  Abstract  
  Address Angers, France  
  Corporate Author Thesis  
  Publisher ICEIS Press Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 972-98816-3-4 Medium  
  Area Expedition Conference PRIS'03  
  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ LVS2003 Serial 1576  
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Author Zhengying Liu; Zhen Xu; Shangeth Rajaa; Meysam Madadi; Julio C. S. Jacques Junior; Sergio Escalera; Adrien Pavao; Sebastien Treguer; Wei-Wei Tu; Isabelle Guyon edit   pdf
url  openurl
  Title Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019 Type Conference Article
  Year 2020 Publication (down) Proceedings of Machine Learning Research Abbreviated Journal  
  Volume 123 Issue Pages 242-252  
  Keywords  
  Abstract We present the design and results of recent competitions in Automated Deep Learning (AutoDL). In the AutoDL challenge series 2019, we organized 5 machine learning challenges: AutoCV, AutoCV2, AutoNLP, AutoSpeech and AutoDL. The first 4 challenges concern each a specific application domain, such as computer vision, natural language processing and speech recognition. At the time of March 2020, the last challenge AutoDL is still on-going and we only present its design. Some highlights of this work include: (1) a benchmark suite of baseline AutoML solutions, with emphasis on domains for which Deep Learning methods have had prior success (image, video, text, speech, etc); (2) a novel any-time learning framework, which opens doors for further theoretical consideration; (3) a repository of around 100 datasets (from all above domains) over half of which are released as public datasets to enable research on meta-learning; (4) analyses revealing that winning solutions generalize to new unseen datasets, validating progress towards universal AutoML solution; (5) open-sourcing of the challenge platform, the starting kit, the dataset formatting toolkit, and all winning solutions (All information available at {autodl.chalearn.org}).  
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  Area Expedition Conference NEURIPS  
  Notes HUPBA Approved no  
  Call Number Admin @ si @ LXR2020 Serial 3500  
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Author Meysam Madadi; Hugo Bertiche; Wafa Bouzouita; Isabelle Guyon; Sergio Escalera edit   pdf
url  openurl
  Title Learning Cloth Dynamics: 3D+Texture Garment Reconstruction Benchmark Type Conference Article
  Year 2021 Publication (down) Proceedings of Machine Learning Research Abbreviated Journal  
  Volume 133 Issue Pages 57-76  
  Keywords  
  Abstract Human avatars are important targets in many computer applications. Accurately tracking, capturing, reconstructing and animating the human body, face and garments in 3D are critical for human-computer interaction, gaming, special effects and virtual reality. In the past, this has required extensive manual animation. Regardless of the advances in human body and face reconstruction, still modeling, learning and analyzing human dynamics need further attention. In this paper we plan to push the research in this direction, e.g. understanding human dynamics in 2D and 3D, with special attention to garments. We provide a large-scale dataset (more than 2M frames) of animated garments with variable topology and type, calledCLOTH3D++. The dataset contains RGBA video sequences paired with its corresponding 3D data. We pay special care to garment dynamics and realistic rendering of RGB data, including lighting, fabric type and texture. With this dataset, we hold a competition at NeurIPS2020. We design three tracks so participants can compete to develop the best method to perform 3D garment reconstruction in a sequence from (1) 3D-to-3D garments, (2) RGB-to-3D garments, and (3) RGB-to-3D garments plus texture. We also provide a baseline method, based on graph convolutional networks, for each track. Baseline results show that there is a lot of room for improvements. However, due to the challenging nature of the problem, no participant could outperform the baselines.  
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  Notes HUPBA; no proj Approved no  
  Call Number Admin @ si @ MBB2021 Serial 3655  
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Author Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; J. Mauri; E. Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E. Esplugas edit   pdf
openurl 
  Title Optimal Stent Implantation: Three-dimensional Evaluation of the Mutual Position of Stent and Vessel via Intracoronary Ecography Type Conference Article
  Year 1999 Publication (down) Proceedings of International Conference on Computer in Cardiology (CIC´99) Abbreviated Journal  
  Volume Issue Pages  
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  Abstract We present a new automatic technique to visualize and quantify the mutual position between the stent and the vessel wall by considering their three-dimensional reconstruction. Two deformable generalized cylinders adapt to the image features in all IVUS planes corresponding to the vessel wall and the stent in order to reconstruct the boundaries of the stent and the vessel in space. The image features that characterize the stent and the vessel wall are determined in terms of edge and ridge image detectors taking into account the gray level of the image pixels. We show that the 30 reconstruction by deformable cylinders is accurate and robust due to the spatial data coherence in the considered volumetric IVUS image. The main clinic utility of the stent and vessel reconstruction by deformable’ cylinders consists of its possibility to visualize and to assess the optimal stent introduction.  
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  Notes MILAB; RV; IAM; ADAS; HuPBA Approved no  
  Call Number IAM @ iam @ CRP1999a Serial 1491  
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Author Cristina Cañero; Petia Radeva; Oriol Pujol; Ricardo Toledo; Debora Gil; J. Saludes; Juan J. Villanueva; B. Garcia del Blanco; Josefina Mauri; Eduard Fernandez-Nofrerias; J.A. Gomez-Hospital; E. Iraculis; J. Comin; C. Quiles; F. Jara; A. Cequier; E.Esplugas edit   pdf
openurl 
  Title Three-dimensional reconstruction and quantification of the coronary tree using intravascular ultrasound images Type Conference Article
  Year 1999 Publication (down) Proceedings of International Conference on Computer in Cardiology (CIC´99) Abbreviated Journal  
  Volume Issue Pages  
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  Abstract In this paper we propose a new Computer Vision technique to reconstruct the vascular wall in space using a deformable model-based technique and compounding methods, based in biplane angiography and intravascular ultrasound data jicsion. It is also proposed a generalpurpose three-dimensional guided interpolation method. The three dimensional centerline of the vessel is reconstructed from geometrically corrected biplane angiographies using automatic segmentation methods and snakes. The IVUS image planes are located in the threedimensional space and correctly oriented. A led interpolation method based in B-SurJaces and snakes isused to fill the gaps among image planes  
  Address  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CINC99  
  Notes MILAB;RV;IAM;ADAS;HuPBA Approved no  
  Call Number IAM @ iam @ CRP1999b Serial 1492  
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Author German Ros; J. Guerrero; Angel Sappa; Antonio Lopez edit   pdf
doi  isbn
openurl 
  Title VSLAM pose initialization via Lie groups and Lie algebras optimization Type Conference Article
  Year 2013 Publication (down) Proceedings of IEEE International Conference on Robotics and Automation Abbreviated Journal  
  Volume Issue Pages 5740 - 5747  
  Keywords SLAM  
  Abstract We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm.  
  Address Karlsruhe; Germany; May 2013  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN 1050-4729 ISBN 978-1-4673-5641-1 Medium  
  Area Expedition Conference ICRA  
  Notes ADAS; 600.054; 600.055; 600.057 Approved no  
  Call Number Admin @ si @ RGS2013a; ADAS @ adas @ Serial 2225  
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Author Petia Radeva; Jordi Vitria edit  openurl
  Title Region-Based Approach for Discriminant Snakes Type Miscellaneous
  Year 2001 Publication (down) Proceedings of ICIP Abbreviated Journal  
  Volume Issue Pages  
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  Address Thesaloniki, Greece  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes OR;MILAB;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ RaV2001 Serial 436  
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Author Gemma Sanchez; Ernest Valveny; Josep Llados; Enric Marti; Oriol Ramos Terrades; N.Lozano; Joan Mas edit  openurl
  Title A system for virtual prototyping of architectural projects Type Conference Article
  Year 2003 Publication (down) Proceedings of Fifth IAPR International Workshop on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 65-74  
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  Area Expedition Conference  
  Notes DAG;IAM Approved no  
  Call Number IAM @ iam @ SVL2003 Serial 1650  
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