toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Adriana Romero; Carlo Gatta; Gustavo Camps-Valls edit   pdf
openurl 
  Title Unsupervised Deep Feature Extraction Of Hyperspectral Images Type Conference Article
  Year 2014 Publication 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Abbreviated Journal  
  Volume Issue Pages  
  Keywords Convolutional networks; deep learning; sparse learning; feature extraction; hyperspectral image classification  
  Abstract This paper presents an effective unsupervised sparse feature learning algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract representations of data, while higher layers represent more abstract and complex characteristics. We successfully illustrate the performance of the extracted representations in a challenging AVIRIS hyperspectral image classification problem, compared to standard dimensionality reduction methods like principal component analysis (PCA) and its kernel counterpart (kPCA). The proposed method largely outperforms the previous state-ofthe-art results on the same experimental setting. Results show that single layer networks can extract powerful discriminative features only when the receptive field accounts for neighboring pixels. Regarding the deep architecture, we can conclude that: (1) additional layers in a deep architecture significantly improve the performance w.r.t. single layer variants; (2) the max-pooling step in each layer is mandatory to achieve satisfactory results; and (3) the performance gain w.r.t. the number of layers is upper bounded, since the spatial resolution is reduced at each pooling, resulting in too spatially coarse output features.  
  Address Lausanne; Switzerland; June 2014  
  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 (down) WHISPERS  
  Notes MILAB; LAMP; 600.079 Approved no  
  Call Number Admin @ si @ RGC2014 Serial 2513  
Permanent link to this record
 

 
Author Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate edit   pdf
openurl 
  Title Local Analysis of Confidence Measures for Optical Flow Quality Evaluation Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages 450-457  
  Keywords Optical Flow; Confidence Measure; Performance Evaluation.  
  Abstract Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance.
 
  Address Lisboa; January 2014  
  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 (down) VISAPP  
  Notes IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 Approved no  
  Call Number Admin @ si @ MGM2014 Serial 2432  
Permanent link to this record
 

 
Author Q. Xue; Laura Igual; A. Berenguel; M. Guerrieri; L. Garrido edit   pdf
openurl 
  Title Active Contour Segmentation with Affine Coordinate-Based Parametrization Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 5-14  
  Keywords Active Contours; Affine Coordinates; Mean Value Coordinates  
  Abstract In this paper, we present a new framework for image segmentation based on parametrized active contours. The contour and the points of the image space are parametrized using a set of reduced control points that have to form a closed polygon in two dimensional problems and a closed surface in three dimensional problems. By moving the control points, the active contour evolves. We use mean value coordinates as the parametrization tool for the interface, which allows to parametrize any point of the space, inside or outside the closed polygon
or surface. Region-based energies such as the one proposed by Chan and Vese can be easily implemented in both two and three dimensional segmentation problems. We show the usefulness of our approach with several experiments.
 
  Address Lisboa; January 2014  
  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 (down) VISAPP  
  Notes OR;MILAB Approved no  
  Call Number Admin @ si @ XIB2014 Serial 2452  
Permanent link to this record
 

 
Author P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa edit   pdf
doi  openurl
  Title Performance Evaluation of Feature Point Descriptors in the Infrared Domain Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 545-550  
  Keywords Infrared Imaging; Feature Point Descriptors  
  Abstract This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered.  
  Address Lisboa; Portugal; January 2014  
  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 (down) VISAPP  
  Notes ADAS; 600.055; 600.076 Approved no  
  Call Number Admin @ si @ RCA2014b Serial 2476  
Permanent link to this record
 

 
Author Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa edit   pdf
doi  openurl
  Title Cross-spectral Stereo Correspondence using Dense Flow Fields Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages 613-617  
  Keywords Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum  
  Abstract This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach.  
  Address Lisboa; Portugal; January 2014  
  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 (down) VISAPP  
  Notes ADAS; 600.055; 600.076 Approved no  
  Call Number Admin @ si @ OAV2014 Serial 2477  
Permanent link to this record
 

 
Author Ariel Amato; Felipe Lumbreras; Angel Sappa edit   pdf
openurl 
  Title A General-purpose Crowdsourcing Platform for Mobile Devices Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages 211-215  
  Keywords Crowdsourcing Platform; Mobile Crowdsourcing  
  Abstract This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform.  
  Address Lisboa; Portugal; January 2014  
  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 (down) VISAPP  
  Notes ISE; ADAS; 600.054; 600.055; 600.076; 600.078 Approved no  
  Call Number Admin @ si @ ALS2014 Serial 2478  
Permanent link to this record
 

 
Author Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen edit   pdf
doi  isbn
openurl 
  Title Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging Type Conference Article
  Year 2014 Publication 17th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal  
  Volume 8896 Issue Pages 231-238  
  Keywords Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging  
  Abstract Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP.
 
  Address Boston; USA; September 2014  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-14677-5 Medium  
  Area Expedition Conference (down) STACOM  
  Notes IAM; ADAS; 600.060; 601.145; 600.076; 600.075 Approved no  
  Call Number Admin @ si @ MKF2014 Serial 2495  
Permanent link to this record
 

 
Author Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester edit   pdf
doi  openurl
  Title Anatomical parameterization for volumetric meshing of the liver Type Conference Article
  Year 2014 Publication SPIE – Medical Imaging Abbreviated Journal  
  Volume 9036 Issue Pages  
  Keywords Coordinate System; Anatomy Modeling; Parameterization  
  Abstract A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at sites
of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the
volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference.
 
  Address Amsterdam; September 2014  
  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 (down) SPIE-MI  
  Notes IAM; 600.075 Approved no  
  Call Number Admin @ si @ VGG2014 Serial 2456  
Permanent link to this record
 

 
Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  openurl
  Title Fast Structural Matching for Document Image Retrieval through Spatial Databases Type Conference Article
  Year 2014 Publication Document Recognition and Retrieval XXI Abbreviated Journal  
  Volume 9021 Issue Pages  
  Keywords Document image retrieval; distance transform; MSER; spatial database  
  Abstract The structure of document images plays a signi cant role in document analysis thus considerable e orts have been made towards extracting and understanding document structure, usually in the form of layout analysis approaches. In this paper, we rst employ Distance Transform based MSER (DTMSER) to eciently extract stable document structural elements in terms of a dendrogram of key-regions. Then a fast structural matching method is proposed to query the structure of document (dendrogram) based on a spatial database which facilitates the formulation of advanced spatial queries. The experiments demonstrate a signi cant improvement in a document retrieval scenario when compared to the use of typical Bag of Words (BoW) and pyramidal BoW descriptors.  
  Address Amsterdam; September 2014  
  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 (down) SPIE-DRR  
  Notes DAG; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ GRK2014a Serial 2496  
Permanent link to this record
 

 
Author Clement Guerin; Christophe Rigaud; Karell Bertet; Jean-Christophe Burie; Arnaud Revel ; Jean-Marc Ogier edit  openurl
  Title Réduction de l’espace de recherche pour les personnages de bandes dessinées Type Conference Article
  Year 2014 Publication 19th National Congress Reconnaissance de Formes et l'Intelligence Artificielle Abbreviated Journal  
  Volume Issue Pages  
  Keywords contextual search; document analysis; comics characters  
  Abstract Les bandes dessinées représentent un patrimoine culturel important dans de nombreux pays et leur numérisation massive offre la possibilité d'effectuer des recherches dans le contenu des images. À ce jour, ce sont principalement les structures des pages et leurs contenus textuels qui ont été étudiés, peu de travaux portent sur le contenu graphique. Nous proposons de nous appuyer sur des éléments déjà étudiés tels que la position des cases et des bulles, pour réduire l'espace de recherche et localiser les personnages en fonction de la queue des bulles. L'évaluation de nos différentes contributions à partir de la base eBDtheque montre un taux de détection des queues de bulle de 81.2%, de localisation des personnages allant jusqu'à 85% et un gain d'espace de recherche de plus de 50%.  
  Address Rouen; Francia; July 2014  
  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 (down) RFIA  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GRB2014 Serial 2480  
Permanent link to this record
 

 
Author Alejandro Tabas; Emili Balaguer-Ballester; Laura Igual edit   pdf
doi  isbn
openurl 
  Title Spatial Discriminant ICA for RS-fMRI characterisation Type Conference Article
  Year 2014 Publication 4th International Workshop on Pattern Recognition in Neuroimaging Abbreviated Journal  
  Volume Issue Pages 1-4  
  Keywords  
  Abstract Resting-State fMRI (RS-fMRI) is a brain imaging technique useful for exploring functional connectivity. A major point of interest in RS-fMRI analysis is to isolate connectivity patterns characterising disorders such as for instance ADHD. Such characterisation is usually performed in two steps: first, all connectivity patterns in the data are extracted by means of Independent Component Analysis (ICA); second, standard statistical tests are performed over the extracted patterns to find differences between control and clinical groups. In this work we introduce a novel, single-step, approach for this problem termed Spatial Discriminant ICA. The algorithm can efficiently isolate networks of functional connectivity characterising a clinical group by combining ICA and a new variant of the Fisher’s Linear Discriminant also introduced in this work. As the characterisation is carried out in a single step, it potentially provides for a richer characterisation of inter-class differences. The algorithm is tested using synthetic and real fMRI data, showing promising results in both experiments.  
  Address Tübingen; June 2014  
  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 978-1-4799-4150-6 Medium  
  Area Expedition Conference (down) PRNI  
  Notes OR;MILAB Approved no  
  Call Number Admin @ si @ TBI2014 Serial 2493  
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  
  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 (down) NIPS  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ ZLX2014 Serial 2621  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit  openurl
  Title Scene Text Recognition: No Country for Old Men? Type Conference Article
  Year 2014 Publication 1st International Workshop on Robust Reading Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  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 (down) IWRR  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GoK2014c Serial 2538  
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  
  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 (down) INCOS  
  Notes OR; HuPBA;MV Approved no  
  Call Number Admin @ si @ ABB2014 Serial 2620  
Permanent link to this record
 

 
Author Jiaolong Xu; Sebastian Ramos;David Vazquez; Antonio Lopez edit   pdf
doi  openurl
  Title Cost-sensitive Structured SVM for Multi-category Domain Adaptation Type Conference Article
  Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3886 - 3891  
  Keywords Domain Adaptation; Pedestrian Detection  
  Abstract Domain adaptation addresses the problem of accuracy drop that a classifier may suffer when the training data (source domain) and the testing data (target domain) are drawn from different distributions. In this work, we focus on domain adaptation for structured SVM (SSVM). We propose a cost-sensitive domain adaptation method for SSVM, namely COSS-SSVM. In particular, during the re-training of an adapted classifier based on target and source data, the idea that we explore consists in introducing a non-zero cost even for correctly classified source domain samples. Eventually, we aim to learn a more targetoriented classifier by not rewarding (zero loss) properly classified source-domain training samples. We assess the effectiveness of COSS-SSVM on multi-category object recognition.  
  Address Stockholm; Sweden; August 2014  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1051-4651 ISBN Medium  
  Area Expedition Conference (down) ICPR  
  Notes ADAS; 600.057; 600.054; 601.217; 600.076 Approved no  
  Call Number ADAS @ adas @ XRV2014a Serial 2434  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: