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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes edit   pdf
openurl 
  Title Représentation par graphe de mots manuscrits dans les images pour la recherche par similarité Type Conference Article
  Year 2014 Publication Colloque International Francophone sur l'Écrit et le Document Abbreviated Journal  
  Volume Issue Pages 233-248  
  Keywords word spotting; graph-based representation; shape context description; graph edit distance; DTW; block merging; query by example  
  Abstract Effective information retrieval on handwritten document images has always been
a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labeled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment results introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods.
 
  Address Nancy; Francia; March 2014  
  Corporate Author Thesis (up)  
  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 CIFED  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ WEG2014c Serial 2564  
Permanent link to this record
 

 
Author Michal Drozdzal; Jordi Vitria; Santiago Segui; Carolina Malagelada; Fernando Azpiroz; Petia Radeva edit  doi
openurl 
  Title Intestinal event segmentation for endoluminal video analysis Type Conference Article
  Year 2014 Publication 21st IEEE International Conference on Image Processing Abbreviated Journal  
  Volume Issue Pages 3592 - 3596  
  Keywords  
  Abstract  
  Address Paris; Francia; October 2014  
  Corporate Author Thesis (up)  
  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 ICIP  
  Notes MILAB; OR;MV Approved no  
  Call Number Admin @ si @ DVS2014 Serial 2565  
Permanent link to this record
 

 
Author Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta edit  doi
isbn  openurl
  Title The ICDAR/GREC 2013 Music Scores Competition: Staff Removal Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 207-220  
  Keywords Competition; Graphics recognition; Music scores; Writer identification; 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 in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Springer Berlin Heidelberg Place of Publication Editor B.Lamiroy; J.-M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077; 600.061 Approved no  
  Call Number Admin @ si @ FKV2014 Serial 2581  
Permanent link to this record
 

 
Author Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez edit  openurl
  Title 3d Pedestrian Detection via Random Forest Type Miscellaneous
  Year 2014 Publication European Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 231-238  
  Keywords Pedestrian Detection  
  Abstract Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications.
 
  Address Zurich; suiza; September 2014  
  Corporate Author Thesis (up)  
  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 ECCV-Demo  
  Notes ADAS; 600.076 Approved no  
  Call Number Admin @ si @ VRR2014 Serial 2570  
Permanent link to this record
 

 
Author Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika edit  openurl
  Title Facial Expression Recognition based on Multi-view Observations with Application to Social Robotics Type Conference Article
  Year 2014 Publication 1st Workshop on Computer Vision for Affective Computing Abbreviated Journal  
  Volume Issue Pages 1-8  
  Keywords  
  Abstract Human-robot interaction is a hot topic nowadays in the social robotics community. One crucial aspect is represented by the affective communication which comes encoded through the facial expressions. In this paper, we propose a novel approach for facial expression recognition, which exploits an efficient and adaptive graph-based label propagation (semi-supervised mode) in a multi-observation framework. The facial features are extracted using an appearance-based 3D face tracker, view- and texture independent. Our method has been extensively tested on the CMU dataset, and has been conveniently compared with other methods for graph construction. With the proposed approach, we developed an application for an AIBO robot, in which it mirrors the recognized facial
expression.
 
  Address Singapore; November 2014  
  Corporate Author Thesis (up)  
  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 ACCV  
  Notes LAMP; Approved no  
  Call Number Admin @ si @ RBD2014 Serial 2599  
Permanent link to this record
 

 
Author Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio edit  doi
openurl 
  Title A computational framework for cancer response assessment based on oncological PET-CT scans Type Journal Article
  Year 2014 Publication Computers in Biology and Medicine Abbreviated Journal CBM  
  Volume 55 Issue Pages 92–99  
  Keywords Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis  
  Abstract In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks.  
  Address  
  Corporate Author Thesis (up)  
  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  
  Notes HuPBA;MILAB Approved no  
  Call Number Admin @ si @ SED2014 Serial 2606  
Permanent link to this record
 

 
Author Maedeh Aghaei; Petia Radeva edit  doi
isbn  openurl
  Title Bag-of-Tracklets for Person Tracking in Life-Logging Data Type Conference Article
  Year 2014 Publication 17th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal  
  Volume 269 Issue Pages 35-44  
  Keywords  
  Abstract By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-61499-451-0 Medium  
  Area Expedition Conference CCIA  
  Notes MILAB Approved no  
  Call Number Admin @ si @ AgR2015 Serial 2607  
Permanent link to this record
 

 
Author R. Clariso; David Masip; A. Rius edit  url
openurl 
  Title Student projects empowering mobile learning in higher education Type Journal
  Year 2014 Publication Revista de Universidad y Sociedad del Conocimiento Abbreviated Journal RUSC  
  Volume 11 Issue Pages 192-207  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis (up)  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1698-580X ISBN Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ CMR2014 Serial 2619  
Permanent link to this record
 

 
Author Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto edit  doi
isbn  openurl
  Title Va-ID: A trust-based virtual assessment system Type Conference Article
  Year 2014 Publication 6th International Conference on Intelligent Networking and Collaborative Systems Abbreviated Journal  
  Volume Issue Pages 328 - 335  
  Keywords  
  Abstract Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model.  
  Address Salerna; Italy; September 2014  
  Corporate Author Thesis (up)  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4799-6386-7 Medium  
  Area Expedition Conference INCOS  
  Notes OR; HuPBA;MV Approved no  
  Call Number Admin @ si @ ABB2014 Serial 2620  
Permanent link to this record
 

 
Author B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva edit  url
openurl 
  Title Learning Deep Features for Scene Recognition using Places Database Type Conference Article
  Year 2014 Publication 28th Annual Conference on Neural Information Processing Systems Abbreviated Journal  
  Volume Issue Pages 487-495  
  Keywords  
  Abstract  
  Address Montreal; Canada; December 2014  
  Corporate Author Thesis (up)  
  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 NIPS  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ ZLX2014 Serial 2621  
Permanent link to this record
 

 
Author Agata Lapedriza; David Masip; David Sanchez edit  doi
isbn  openurl
  Title Emotions Classification using Facial Action Units Recognition Type Conference Article
  Year 2014 Publication 17th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal  
  Volume 269 Issue Pages 55-64  
  Keywords  
  Abstract In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-61499-451-0 Medium  
  Area Expedition Conference CCIA  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ LMS2014 Serial 2622  
Permanent link to this record
 

 
Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 25-37  
  Keywords  
  Abstract Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ BDJ2014 Serial 2699  
Permanent link to this record
 

 
Author Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit  doi
isbn  openurl
  Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 3-10  
  Keywords  
  Abstract In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.055; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ RKL2014 Serial 2700  
Permanent link to this record
 

 
Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Classification of Administrative Document Images by Logo Identification Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 49-58  
  Keywords Administrative Document Classification; Logo Recognition; Logo Spotting  
  Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.  
  Address  
  Corporate Author Thesis (up)  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.045; 605.203; 600.077 Approved no  
  Call Number Admin @ si @ RPK2014 Serial 2701  
Permanent link to this record
 

 
Author Ariel Amato edit  openurl
  Title Moving cast shadow detection Type Journal Article
  Year 2014 Publication Electronic letters on computer vision and image analysis Abbreviated Journal ELCVIA  
  Volume 13 Issue 2 Pages 70-71  
  Keywords  
  Abstract Motion perception is an amazing innate ability of the creatures on the planet. This adroitness entails a functional advantage that enables species to compete better in the wild. The motion perception ability is usually employed at different levels, allowing from the simplest interaction with the ’physis’ up to the most transcendental survival tasks. Among the five classical perception system , vision is the most widely used in the motion perception field. Millions years of evolution have led to a highly specialized visual system in humans, which is characterized by a tremendous accuracy as well as an extraordinary robustness. Although humans and an immense diversity of species can distinguish moving object with a seeming simplicity, it has proven to be a difficult and non trivial problem from a computational perspective. In the field of Computer Vision, the detection of moving objects is a challenging and fundamental research area. This can be referred to as the ’origin’ of vast and numerous vision-based research sub-areas. Nevertheless, from the bottom to the top of this hierarchical analysis, the foundations still relies on when and where motion has occurred in an image. Pixels corresponding to moving objects in image sequences can be identified by measuring changes in their values. However, a pixel’s value (representing a combination of color and brightness) could also vary due to other factors such as: variation in scene illumination, camera noise and nonlinear sensor responses among others. The challenge lies in detecting if the changes in pixels’ value are caused by a genuine object movement or not. An additional challenging aspect in motion detection is represented by moving cast shadows. The paradox arises because a moving object and its cast shadow share similar motion patterns. However, a moving cast shadow is not a moving object. In fact, a shadow represents a photometric illumination effect caused by the relative position of the object with respect to the light sources. Shadow detection methods are mainly divided in two domains depending on the application field. One normally consists of static images where shadows are casted by static objects, whereas the second one is referred to image sequences where shadows are casted by moving objects. For the first case, shadows can provide additional geometric and semantic cues about shape and position of its casting object as well as the localization of the light source. Although the previous information can be extracted from static images as well as video sequences, the main focus in the second area is usually change detection, scene matching or surveillance. In this context, a shadow can severely affect with the analysis and interpretation of the scene. The work done in the thesis is focused on the second case, thus it addresses the problem of detection and removal of moving cast shadows in video sequences in order to enhance the detection of moving object.  
  Address  
  Corporate Author Thesis (up)  
  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  
  Notes ISE Approved no  
  Call Number Admin @ si @ Ama2014 Serial 2870  
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