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Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu
Title New Opportunities for Computer Vision-Based Assistive Technology Systems for the Visually Impaired Type Journal Article
Year 2014 Publication Computer Abbreviated Journal COMP
Volume 47 Issue 4 Pages 52-58
Keywords
Abstract Computing advances and increased smartphone use gives technology system designers greater flexibility in exploiting computer vision to support visually impaired users. Understanding these users' needs will certainly provide insight for the development of improved usability of computing devices.
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 0018-9162 ISBN Medium
Area Expedition Conference
Notes OR;MV Approved no
Call Number Admin @ si @ TSR2014a Serial 2317
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Author Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras
Title ICDAR 2013 Robust Reading Competition Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1484-1493
Keywords
Abstract This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.
Address Washington; USA; August 2013
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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; 600.056 Approved no
Call Number Admin @ si @ KSU2013 Serial 2318
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Author Lluis Gomez; Dimosthenis Karatzas
Title Multi-script Text Extraction from Natural Scenes Type Conference Article
Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 467-471
Keywords
Abstract Scene text extraction methodologies are usually based in classification of individual regions or patches, using a priori knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organisation through which text emerges as a perceptually significant group of atomic objects. Therefore humans are able to detect text even in languages and scripts never seen before. In this paper, we argue that the text extraction problem could be posed as the detection of meaningful groups of regions. We present a method built around a perceptual organisation framework that exploits collaboration of proximity and similarity laws to create text-group hypotheses. Experiments demonstrate that our algorithm is competitive with state of the art approaches on a standard dataset covering text in variable orientations and two languages.
Address Washington; USA; August 2013
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 1520-5363 ISBN Medium
Area Expedition Conference ICDAR
Notes DAG; 600.056; 601.158; 601.197 Approved no
Call Number Admin @ si @ GoK2013 Serial 2310
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Author Adriana Romero; Carlo Gatta
Title Do We Really Need All These Neurons? Type Conference Article
Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 7887 Issue Pages 460--467
Keywords Retricted Boltzmann Machine; hidden units; unsupervised learning; classification
Abstract Restricted Boltzmann Machines (RBMs) are generative neural networks that have received much attention recently. In particular, choosing the appropriate number of hidden units is important as it might hinder their representative power. According to the literature, RBM require numerous hidden units to approximate any distribution properly. In this paper, we present an experiment to determine whether such amount of hidden units is required in a classification context. We then propose an incremental algorithm that trains RBM reusing the previously trained parameters using a trade-off measure to determine the appropriate number of hidden units. Results on the MNIST and OCR letters databases show that using a number of hidden units, which is one order of magnitude smaller than the literature estimate, suffices to achieve similar performance. Moreover, the proposed algorithm allows to estimate the required number of hidden units without the need of training many RBM from scratch.
Address Madeira; Portugal; June 2013
Corporate Author Thesis (up)
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 978-3-642-38627-5 Medium
Area Expedition Conference IbPRIA
Notes MILAB; 600.046 Approved no
Call Number Admin @ si @ RoG2013 Serial 2311
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Author Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu
Title Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition Type Conference Article
Year 2013 Publication Human Behavior Understanding 4th International Workshop Abbreviated Journal
Volume 8212 Issue Pages 124-135
Keywords
Abstract Workshop on Human Behavior Understanding
Human-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods.
Address Barcelona
Corporate Author Thesis (up)
Publisher Springer International Publishing 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 978-3-319-02713-5 Medium
Area Expedition Conference HBU
Notes OR;MV Approved no
Call Number Admin @ si @ DBR2013 Serial 2315
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Author Bogdan Raducanu; Fadi Dornaika
Title Embedding new observations via sparse-coding for non-linear manifold learning Type Journal Article
Year 2014 Publication Pattern Recognition Abbreviated Journal PR
Volume 47 Issue 1 Pages 480-492
Keywords
Abstract Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes.
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 OR;MV Approved no
Call Number Admin @ si @ RaD2013b Serial 2316
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Author Albert Gordo; Florent Perronnin; Ernest Valveny
Title Large-scale document image retrieval and classification with runlength histograms and binary embeddings Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 7 Pages 1898-1905
Keywords visual document descriptor; compression; large-scale; retrieval; classification
Abstract We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be
computed efficiently. We show how this descriptor can achieve state-of-theart
results on two very different public datasets in classification and retrieval
tasks. Moreover, we show how we can compress and binarize these descriptors
to make them suitable for large-scale applications. We can achieve state-ofthe-
art results in classification using binary descriptors of as few as 16 to 64
bits.
Address
Corporate Author Thesis (up)
Publisher Elsevier Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG; 600.042; 600.045; 605.203 Approved no
Call Number Admin @ si @ GPV2013 Serial 2306
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Author Albert Gordo; Alicia Fornes; Ernest Valveny
Title Writer identification in handwritten musical scores with bags of notes Type Journal Article
Year 2013 Publication Pattern Recognition Abbreviated Journal PR
Volume 46 Issue 5 Pages 1337-1345
Keywords
Abstract Writer Identification is an important task for the automatic processing of documents. However, the identification of the writer in graphical documents is still challenging. In this work, we adapt the Bag of Visual Words framework to the task of writer identification in handwritten musical scores. A vanilla implementation of this method already performs comparably to the state-of-the-art. Furthermore, we analyze the effect of two improvements of the representation: a Bhattacharyya embedding, which improves the results at virtually no extra cost, and a Fisher Vector representation that very significantly improves the results at the cost of a more complex and costly representation. Experimental evaluation shows results more than 20 points above the state-of-the-art in a new, challenging dataset.
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 0031-3203 ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ GFV2013 Serial 2307
Permanent link to this record
 
 
Author David Fernandez; Simone Marinai; Josep Llados; Alicia Fornes
Title Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks Type Conference Article
Year 2013 Publication 2nd International Workshop on Historical Document Imaging and Processing Abbreviated Journal
Volume Issue Pages 36-43
Keywords
Abstract Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.
Address washington; USA; August 2013
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 978-1-4503-2115-0 Medium
Area Expedition Conference HIP
Notes DAG; 600.056; 600.045; 600.061; 602.006 Approved no
Call Number Admin @ si @ FML2013 Serial 2308
Permanent link to this record
 
 
Author A. M. Here; B. C. Lopez; Debora Gil; J. J. Camarero; Jordi Martinez-Vilalta
Title A new software to analyse wood anatomical features in conifer species Type Conference Article
Year 2013 Publication International Symposium on Wood Structure in Plant Biology and Ecology Abbreviated Journal
Volume Issue Pages
Keywords
Abstract International Symposium on Wood Structure in Plant Biology and Ecology
Address Naples; Italy; March 2013
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 WSE
Notes IAM Approved no
Call Number Admin @ si @ HLG2013 Serial 2303
Permanent link to this record
 
 
Author Enric Marti; Ferran Poveda; Antoni Gurgui; Jaume Rocarias; Debora Gil
Title Una propuesta de seguimiento, tutorías on line y evaluación en la metodología de Aprendizaje Basado en Proyectos Type Miscellaneous
Year 2013 Publication IV Congreso Internacional UNIVEST Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Poster
Address Girona
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 UNIVEST
Notes IAM Approved no
Call Number Admin @ si @ MPG2013a Serial 2304
Permanent link to this record
 
 
Author Debora Gil; Agnes Borras; Sergio Vera; Miguel Angel Gonzalez Ballester
Title A Validation Benchmark for Assessment of Medial Surface Quality for Medical Applications Type Conference Article
Year 2013 Publication 9th International Conference on Computer Vision Systems Abbreviated Journal
Volume 7963 Issue Pages 334-343
Keywords Medial Surfaces; Shape Representation; Medical Applications; Performance Evaluation
Abstract Confident use of medial surfaces in medical decision support systems requires evaluating their quality for detecting pathological deformations and describing anatomical volumes. Validation in the medical imaging field is a challenging task mainly due to the difficulties for getting consensual ground truth. In this paper we propose a validation benchmark for assessing medial surfaces in the context of medical applications. Our benchmark includes a home-made database of synthetic medial surfaces and volumes and specific scores for evaluating surface accuracy, its stability against volume deformations and its capabilities for accurate reconstruction of anatomical volumes.
Address Sant Petersburg; Russia; July 2013
Corporate Author Thesis (up)
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 978-3-642-39401-0 Medium
Area Expedition Conference ICVS
Notes IAM; 600.044; 600.060 Approved no
Call Number Admin @ si @ GBV2013 Serial 2300
Permanent link to this record
 
 
Author Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil
Title Volumetric Anatomical Parameterization and Meshing for Inter-patient Liver Coordinate System Deffinition Type Conference Article
Year 2013 Publication 16th International Conference on Medical Image Computing and Computer Assisted Intervention Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Nagoya; Japan; September 2013
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 MICCAI
Notes IAM Approved no
Call Number Admin @ si @ VGG2013 Serial 2301
Permanent link to this record
 
 
Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez
Title On-line lumen centre detection in gastrointestinal and respiratory endoscopy Type Conference Article
Year 2013 Publication Second International Workshop Clinical Image-Based Procedures Abbreviated Journal
Volume 8361 Issue Pages 31-38
Keywords Lumen centre detection; Bronchoscopy; Colonoscopy
Abstract We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).
Address Nagoya; Japan; September 2013
Corporate Author Thesis (up)
Publisher Springer International Publishing Place of Publication Editor Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-319-05665-4 Medium
Area 800 Expedition Conference CLIP
Notes MV; IAM; 600.047; 600.044; 600.060 Approved no
Call Number Admin @ si @ SBG2013 Serial 2302
Permanent link to this record
 
 
Author Volkmar Frinken; Andreas Fischer; Markus Baumgartner; Horst Bunke
Title Keyword spotting for self-training of BLSTM NN based handwriting recognition systems Type Journal Article
Year 2014 Publication Pattern Recognition Abbreviated Journal PR
Volume 47 Issue 3 Pages 1073-1082
Keywords Document retrieval; Keyword spotting; Handwriting recognition; Neural networks; Semi-supervised learning
Abstract The automatic transcription of unconstrained continuous handwritten text requires well trained recognition systems. The semi-supervised paradigm introduces the concept of not only using labeled data but also unlabeled data in the learning process. Unlabeled data can be gathered at little or not cost. Hence it has the potential to reduce the need for labeling training data, a tedious and costly process. Given a weak initial recognizer trained on labeled data, self-training can be used to recognize unlabeled data and add words that were recognized with high confidence to the training set for re-training. This process is not trivial and requires great care as far as selecting the elements that are to be added to the training set is concerned. In this paper, we propose to use a bidirectional long short-term memory neural network handwritten recognition system for keyword spotting in order to select new elements. A set of experiments shows the high potential of self-training for bootstrapping handwriting recognition systems, both for modern and historical handwritings, and demonstrate the benefits of using keyword spotting over previously published self-training schemes.
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 DAG; 600.077; 602.101 Approved no
Call Number Admin @ si @ FFB2014 Serial 2297
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