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Author | H. Chouaib; Oriol Ramos Terrades; Salvatore Tabbone; F. Cloppet; N. Vincent | ||||
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 | T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades | ||||
Title | Symbol Descriptor Based on Shape Context and Vector Model of Information Retrieval | Type | Conference Article | ||
Year | 2008 | Publication | Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, | Abbreviated Journal | |
Volume | Issue | Pages | 191-197 | ||
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Address | Nara, Japan | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | DAS | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ NTR2008a | Serial | 1873 | ||
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Author | H. Chouaib; Salvatore Tabbone; Oriol Ramos Terrades; F. Cloppet; N. Vincent; A.T. Thierry Paquet | ||||
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 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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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 | T.O. Nguyen; Salvatore Tabbone; Oriol Ramos Terrades; A.T. Thierry | ||||
Title | Proposition d'un descripteur de formes et du modèle vectoriel pour la recherche de symboles | Type | Conference Article | ||
Year | 2008 | Publication | Colloque International Francophone sur l'Ecrit et le Document | Abbreviated Journal | |
Volume | Issue | Pages | 79-84 | ||
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Address | Rouen, France | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CIFED | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ NTR2008b | Serial | 1875 | ||
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Author | Salvatore Tabbone; Oriol Ramos Terrades; S. Barrat | ||||
Title | Histogram of radon transform. A useful descriptor for shape retrieval | 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 | ||||
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 | ICPR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ TRB2008 | Serial | 1876 | ||
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Author | Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers | ||||
Title | Adapting Pedestrian Detection from Synthetic to Far Infrared Images | Type | Conference Article | ||
Year | 2013 | Publication | ICCV Workshop on Visual Domain Adaptation and Dataset Bias | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Domain Adaptation; Far Infrared; Pedestrian Detection | ||||
Abstract | We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. | ||||
Address | Sydney; Australia; December 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Sydney, Australy | Editor | ||
Language | English | Summary Language | Original Title | ||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICCVW-VisDA | ||
Notes | ADAS; 600.054; 600.055; 600.057; 601.217;ISE | Approved | no | ||
Call Number | ADAS @ adas @ SRV2013 | Serial | 2334 | ||
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Author | V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta | ||||
Title | The ICDAR/GREC 2013 Music Scores Competition on Staff Removal | Type | Conference Article | ||
Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Competition; Music scores; Staff Removal | ||||
Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. | ||||
Address | Bethlehem; PA; USA; August 2013 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | GREC | ||
Notes | DAG; 600.045; 600.061 | Approved | no | ||
Call Number | Admin @ si @ KFV2013 | Serial | 2337 | ||
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Author | Sergio Escalera; Ana Puig; Oscar Amoros; Maria Salamo | ||||
Title | Intelligent GPGPU Classification in Volume Visualization: a framework based on Error-Correcting Output Codes | Type | Journal Article | ||
Year | 2011 | Publication | Computer Graphics Forum | Abbreviated Journal | CGF |
Volume | 30 | Issue | 7 | Pages | 2107-2115 |
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Abstract | IF JCR 1.455 2010 25/99
In volume visualization, the definition of the regions of interest is inherently an iterative trial-and-error process finding out the best parameters to classify and render the final image. Generally, the user requires a lot of expertise to analyze and edit these parameters through multi-dimensional transfer functions. In this paper, we present a framework of intelligent methods to label on-demand multiple regions of interest. These methods can be split into a two-level GPU-based labelling algorithm that computes in time of rendering a set of labelled structures using the Machine Learning Error-Correcting Output Codes (ECOC) framework. In a pre-processing step, ECOC trains a set of Adaboost binary classifiers from a reduced pre-labelled data set. Then, at the testing stage, each classifier is independently applied on the features of a set of unlabelled samples and combined to perform multi-class labelling. We also propose an alternative representation of these classifiers that allows to highly parallelize the testing stage. To exploit that parallelism we implemented the testing stage in GPU-OpenCL. The empirical results on different data sets for several volume structures shows high computational performance and classification accuracy. |
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Notes | MILAB; HuPBA | Approved | no | ||
Call Number | Admin @ si @ EPA2011 | Serial | 1881 | ||
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Author | Mario Rojas; David Masip; A. Todorov; Jordi Vitria | ||||
Title | Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models | Type | Journal Article | ||
Year | 2011 | Publication | PloS one | Abbreviated Journal | Plos |
Volume | 6 | Issue | 8 | Pages | e23323 |
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Abstract | JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions |
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Publisher | Public Library of Science | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ RMT2011 | Serial | 1883 | ||
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Author | Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu | ||||
Title | Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction | Type | Journal Article | ||
Year | 2012 | Publication | Sensors | Abbreviated Journal | SENS |
Volume | 12 | Issue | 2 | Pages | 1702-1719 |
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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. |
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Publisher | Molecular Diversity Preservation International | Place of Publication | Editor | ||
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Notes | MILAB; OR;HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ EBV2012 | Serial | 1885 | ||
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Author | Ruth Aylett; Ginevra Castellano; Bogdan Raducanu; Ana Paiva; Marc Hanheide | ||||
Title | Long-term socially perceptive and interactive robot companions: challenges and future perspectives | Type | Conference Article | ||
Year | 2011 | Publication | 13th International Conference on Multimodal Interaction | Abbreviated Journal | |
Volume | Issue | Pages | 323-326 | ||
Keywords | human-robot interaction, multimodal interaction, social robotics | ||||
Abstract | This paper gives a brief overview of the challenges for multi-model perception and generation applied to robot companions located in human social environments. It reviews the current position in both perception and generation and the immediate technical challenges and goes on to consider the extra issues raised by embodiment and social context. Finally, it briefly discusses the impact of systems that must function continually over months rather than just for a few hours. | ||||
Address | Alicante | ||||
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Publisher | ACM | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-1-4503-0641-6 | Medium | ||
Area | Expedition | Conference | ICMI | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ ACR2011 | Serial | 1888 | ||
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Author | Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu | ||||
Title | LSDA Solution Schemes for Modelless 3D Head Pose Estimation | Type | Conference Article | ||
Year | 2012 | Publication | IEEE Workshop on the Applications of Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 393-398 | ||
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Address | Breckenridge; USA; | ||||
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Area | Expedition | Conference | WACV | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ DBR2012 | Serial | 1889 | ||
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Author | Antonio Hernandez; Carlos Primo; Sergio Escalera | ||||
Title | Automatic user interaction correction via Multi-label Graph cuts | Type | Conference Article | ||
Year | 2011 | Publication | In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV | Abbreviated Journal | |
Volume | Issue | Pages | 1276-1281 | ||
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Abstract | Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm. | ||||
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ISSN | ISBN | 978-1-4673-0062-9 | Medium | ||
Area | Expedition | Conference | HICV | ||
Notes | MILAB; HuPBA | Approved | no | ||
Call Number | Admin @ si @ HPE2011 | Serial | 1892 | ||
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Author | Miguel Reyes; Gabriel Dominguez; Sergio Escalera | ||||
Title | Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data | Type | Conference Article | ||
Year | 2011 | Publication | 1st IEEE Workshop on Consumer Depth Cameras for Computer Vision | Abbreviated Journal | |
Volume | Issue | Pages | 1182-1188 | ||
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Abstract | We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach. | ||||
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ISSN | ISBN | 978-1-4673-0062-9 | Medium | ||
Area | Expedition | Conference | CDC4CV | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RDE2011 | Serial | 1893 | ||
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Author | Jorge Bernal; David Vazquez (eds) | ||||
Title | Computer vision Trends and Challenges | Type | Book Whole | ||
Year | 2013 | Publication | Computer vision Trends and Challenges | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | CVCRD; Computer Vision | ||||
Abstract | This book contains the papers presented at the Eighth CVC Workshop on Computer Vision Trends and Challenges (CVCR&D'2013). The workshop was held at the Computer Vision Center (Universitat Autònoma de Barcelona), the October 25th, 2013. The CVC workshops provide an excellent opportunity for young researchers and project engineers to share new ideas and knowledge about the progress of their work, and also, to discuss about challenges and future perspectives. In addition, the workshop is the welcome event for new people that recently have joined the institute.
The program of CVCR&D is organized in a single-track single-day workshop. It comprises several sessions dedicated to specific topics. For each session, a doctor working on the topic introduces the general research lines. The PhD students expose their specific research. A poster session will be held for open questions. Session topics cover the current research lines and development projects of the CVC: Medical Imaging, Medical Imaging, Color & Texture Analysis, Object Recognition, Image Sequence Evaluation, Advanced Driver Assistance Systems, Machine Vision, Document Analysis, Pattern Recognition and Applications. We want to thank all paper authors and Program Committee members. Their contribution shows that the CVC has a dynamic, active, and promising scientific community. We hope you all enjoy this Eighth workshop and we are looking forward to meeting you and new people next year in the Ninth CVCR&D. |
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Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | Jorge Bernal; David Vazquez | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-84-940902-2-6 | Medium | ||
Area | Expedition | Conference | |||
Notes | Approved | no | |||
Call Number | ADAS @ adas @ BeV2013 | Serial | 2339 | ||
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