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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames Type (up) Conference Article
Year 2013 Publication 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal
Volume Issue Pages 7350 - 7354
Keywords
Abstract In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.
Address Osaka; Japan; July 2013
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 1557-170X ISBN Medium
Area 800 Expedition Conference EMBC
Notes MV; 600.047; 600.060;SIAI Approved no
Call Number Admin @ si @ BSV2013 Serial 2286
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Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados
Title An interactive appearance-based document retrieval system for historical newspapers Type (up) Conference Article
Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal
Volume Issue Pages 84-87
Keywords
Abstract In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers.
Address Barcelona; February 2013
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 VISAPP
Notes DAG; 600.056; 600.045; 605.203 Approved no
Call Number Admin @ si @ GRK2013a Serial 2290
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Author Isabel Guitart; Jordi Conesa; Luis Villarejo; Agata Lapedriza; David Masip; Antoni Perez; Elena Planas
Title Opinion Mining on Educational Resources at the Open University of Catalonia Type (up) Conference Article
Year 2013 Publication 3rd International Workshop on Adaptive Learning via Interactive, Collaborative and Emotional approaches. In conjunction with CISIS 2013: The 7th International Conference on Complex, Intelligent, and Software Intensive Systems Abbreviated Journal
Volume Issue Pages 385 - 390
Keywords
Abstract In order to make improvements to teaching, it is vital to know what students think of the way they are taught. With that purpose in mind, exhaustively analyzing the forums associated with the subjects taught at the Universitat Oberta de Cataluya (UOC) would be extremely helpful, as the university's students often post comments on their learning experiences in them. Exploiting the content of such forums is not a simple undertaking. The volume of data involved is very large, and performing the task manually would require a great deal of effort from lecturers. As a first step to solve this problem, we propose a tool to automatically analyze the posts in forums of communities of UOC students and teachers, with a view to systematically mining the opinions they contain. This article defines the architecture of such tool and explains how lexical-semantic and language technology resources can be used to that end. For pilot testing purposes, the tool has been used to identify students' opinions on the UOC's Business Intelligence master's degree course during the last two years. The paper discusses the results of such test. The contribution of this paper is twofold. Firstly, it demonstrates the feasibility of using natural language parsing techniques to help teachers to make decisions. Secondly, it introduces a simple tool that can be refined and adapted to a virtual environment for the purpose in question.
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 978-0-7695-4992-7 Medium
Area Expedition Conference ALICE
Notes OR;MV Approved no
Call Number GCV2013 Serial 2268
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Author Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner
Title Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation Type (up) Conference Article
Year 2011 Publication In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage 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 CartoHerit
Notes DAG Approved no
Call Number Admin @ si @ RRL2011b Serial 1978
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Author Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers
Title Improving HOG with Image Segmentation: Application to Human Detection Type (up) Conference Article
Year 2012 Publication 11th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 7517 Issue Pages 178-189
Keywords Segmentation; Pedestrian Detection
Abstract In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function.
Address Brno, Czech Republic
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor J. Blanc-Talon et al.
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-33139-8 Medium
Area Expedition Conference ACIVS
Notes ADAS;ISE Approved no
Call Number ADAS @ adas @ SLV2012 Serial 1980
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Author David Vazquez; Antonio Lopez; Daniel Ponsa
Title Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection Type (up) Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 3492 - 3495
Keywords Pedestrian Detection; Domain Adaptation; Virtual worlds
Abstract Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1).
Address Tsukuba Science City, Japan
Corporate Author Thesis
Publisher IEEE Place of Publication Tsukuba Science City, JAPAN Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1051-4651 ISBN 978-1-4673-2216-4 Medium
Area Expedition Conference ICPR
Notes ADAS Approved no
Call Number ADAS @ adas @ VLP2012 Serial 1981
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Author Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny
Title A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection Type (up) Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 453-458
Keywords
Abstract In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.
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 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number DAG @ dag @ AFF2012 Serial 1983
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Author Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny
Title Efficient Exemplar Word Spotting Type (up) Conference Article
Year 2012 Publication 23rd British Machine Vision Conference Abbreviated Journal
Volume Issue Pages 67.1- 67.11
Keywords
Abstract In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage.
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 1-901725-46-4 Medium
Area Expedition Conference BMVC
Notes DAG Approved no
Call Number DAG @ dag @ AGF2012 Serial 1984
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Author Ferran Poveda; Debora Gil;Enric Marti
Title Multi-resolution DT-MRI cardiac tractography Type (up) Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 270-277
Keywords
Abstract Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture.
Address Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes IAM Approved no
Call Number IAM @ iam @ PGM2012 Serial 1986
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Author Jose Carlos Rubio; Joan Serrat; Antonio Lopez; N. Paragios
Title Image Contextual Representation and Matching through Hierarchies and Higher Order Graphs Type (up) Conference Article
Year 2012 Publication 21st International Conference on Pattern Recognition Abbreviated Journal
Volume Issue Pages 2664 - 2667
Keywords
Abstract We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic objects are represented with a shape descriptor. Many-to-many matching of regions is specially challenging due to the instability of the segmentation under slight image changes, and we explicitly handle it through high order potentials. We demonstrate the matching approach applied to images of world famous buildings, captured under different conditions, showing the robustness of our method to large variations in illumination and viewpoint.
Address Tsukuba Science City, Japan
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 1051-4651 ISBN 978-1-4673-2216-4 Medium
Area Expedition Conference ICPR
Notes ADAS Approved no
Call Number Admin @ si @ RSL2012a; Serial 2032
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Author Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux
Title What a difference in biomechanics cardiac fiber makes Type (up) Conference Article
Year 2012 Publication Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges Abbreviated Journal
Volume 7746 Issue Pages 253-260
Keywords
Abstract Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
Address Nice, France
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-36960-5 Medium
Area Expedition Conference STACOM
Notes IAM Approved no
Call Number IAM @ iam @ GBA2012 Serial 1987
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Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil
Title A medial map capturing the essential geometry of organs Type (up) Conference Article
Year 2012 Publication ISBI Workshop on Open Source Medical Image Analysis software Abbreviated Journal
Volume Issue Pages 1691 - 1694
Keywords Medial Surface Representation, Volume Reconstruction,Geometry , Image reconstruction , Liver , Manifolds , Shape , Surface morphology , Surface reconstruction
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Accurate computation of one pixel wide medial surfaces is mandatory. Those surfaces must represent faithfully the geometry of the volume. Although morphological methods produce excellent results in 2D, their complexity and quality drops across dimensions, due to a more complex description of pixel neighborhoods. This paper introduces a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. Our experiments show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume
Address Barcelona,Spain
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 1945-7928 ISBN 978-1-4577-1857-1 Medium
Area Expedition Conference ISBI
Notes IAM Approved no
Call Number IAM @ iam @ VGG2012a Serial 1989
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Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate
Title A Complete Confidence Framework for Optical Flow Type (up) Conference Article
Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal
Volume 7584 Issue 2 Pages 124-133
Keywords Optical flow, confidence measures, sparsification plots, error prediction plots
Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Florence, Italy, October 7-13, 2012 Editor Andrea Fusiello, Vittorio Murino ,Rita Cucchiara
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-33867-0 Medium
Area Expedition Conference ECCVW
Notes IAM;ADAS; Approved no
Call Number IAM @ iam @ MGH2012b Serial 1991
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Author Ricard Borras; Agata Lapedriza; Laura Igual
Title Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition Type (up) Conference Article
Year 2012 Publication 9th International Conference on Image Analysis and Recognition Abbreviated Journal
Volume 7325 Issue II Pages 98-105
Keywords
Abstract This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems.
Address Aveiro, Portugal
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-31297-7 Medium
Area Expedition Conference ICIAR
Notes OR; MILAB;MV Approved no
Call Number Admin @ si @ BLI2012 Serial 2009
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Author Albert Clapes; Miguel Reyes; Sergio Escalera
Title User Identification and Object Recognition in Clutter Scenes Based on RGB-Depth Analysis Type (up) Conference Article
Year 2012 Publication 7th Conference on Articulated Motion and Deformable Objects Abbreviated Journal
Volume 7378 Issue Pages 1-11
Keywords
Abstract We propose an automatic system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized online using robust statistical approaches over RGBD descriptions. Finally, the system saves the historic of user-object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches.
Address Mallorca
Corporate Author Thesis
Publisher Springer Berlin Heidelberg 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 978-3-642-31566-4 Medium
Area Expedition Conference AMDO
Notes HUPBA;MILAB Approved no
Call Number Admin @ si @ CRE2012 Serial 2010
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