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Author | Marçal Rusiñol; Josep Llados | ||||
Title | Boosting the Handwritten Word Spotting Experience by Including the User in the Loop | Type | Journal Article | ||
Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 47 | Issue | 3 | Pages | 1063–1072 |
Keywords | Handwritten word spotting; Query by example; Relevance feedback; Query fusion; Multidimensional scaling | ||||
Abstract | In this paper, we study the effect of taking the user into account in a query-by-example handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and two baseline word spotting approaches both based on the bag-of-visual-words model. We finally present two alternative ways of presenting the results to the user that might be more attractive and suitable to the user's needs than the classic ranked list. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.045; 600.061; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RuL2013 | Serial | 2343 | ||
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Author | Marçal Rusiñol; Lluis Pere de las Heras; Oriol Ramos Terrades | ||||
Title | Flowchart Recognition for Non-Textual Information Retrieval in Patent Search | Type | Journal Article | ||
Year | 2014 | Publication | Information Retrieval | Abbreviated Journal | IR |
Volume | 17 | Issue | 5-6 | Pages | 545-562 |
Keywords | Flowchart recognition; Patent documents; Text/graphics separation; Raster-to-vector conversion; Symbol recognition | ||||
Abstract | Relatively little research has been done on the topic of patent image retrieval and in general in most of the approaches the retrieval is performed in terms of a similarity measure between the query image and the images in the corpus. However, systems aimed at overcoming the semantic gap between the visual description of patent images and their conveyed concepts would be very helpful for patent professionals. In this paper we present a flowchart recognition method aimed at achieving a structured representation of flowchart images that can be further queried semantically. The proposed method was submitted to the CLEF-IP 2012 flowchart recognition task. We report the obtained results on this dataset. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 1386-4564 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ RHR2013 | Serial | 2342 | ||
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Author | Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol | ||||
Title | Interactive Document Retrieval and Classification. | Type | Book Chapter | ||
Year | 2013 | Publication | Multimodal Interaction in Image and Video Applications | Abbreviated Journal | |
Volume | 48 | Issue | Pages | 17-30 | |
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Abstract | In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents. | ||||
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Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Angel Sappa; Jordi Vitria | |
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Series Volume | Series Issue | Edition | |||
ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ VRM2013 | Serial | 2341 | ||
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Author | Hany Salah Eldeen | ||||
Title | Colour Naming in Context through a Perceptual Model | Type | Report | ||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 130 | Issue | Pages | ||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | ||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Eld2009 | Serial | 2389 | ||
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Author | Naila Murray | ||||
Title | Perceptual Feature Detection | Type | Report | ||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 131 | Issue | Pages | ||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | ||
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Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ Mur2009 | Serial | 2390 | ||
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Author | Josep M. Gonfaus | ||||
Title | Semantic Segmentation of Images Using Random Ferns | Type | Report | ||
Year | 2009 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 132 | Issue | Pages | ||
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Corporate Author | Computer Vision Center | Thesis | Master's thesis | ||
Publisher | Place of Publication | Bellaterra, Barcelona | Editor | ||
Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | |||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ Gon2009 | Serial | 2391 | ||
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Author | Javier Marin; David Geronimo; David Vazquez; Antonio Lopez | ||||
Title | Pedestrian Detection: Exploring Virtual Worlds | Type | Book Chapter | ||
Year | 2012 | Publication | Handbook of Pattern Recognition: Methods and Application | Abbreviated Journal | |
Volume | 5 | Issue | Pages | 145-162 | |
Keywords | Virtual worlds; Pedestrian Detection; Domain Adaptation | ||||
Abstract | Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition. | ||||
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Publisher | iConcept Press | Place of Publication | Editor | ||
Language | English | Summary Language | Original Title | ||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-477554-82-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ MGV2012 | Serial | 1979 | ||
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Author | Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera | ||||
Title | Automatic Human Behavior Analysis in ADHD | Type | Conference Article | ||
Year | 2012 | Publication | Eunethydis 2nd International ADHD Conference | Abbreviated Journal | |
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Abstract | Poster | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | EUNETHYDIS | ||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | Admin @ si @ EMI2012a | Serial | 2058 | ||
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Author | David Geronimo; Antonio Lopez | ||||
Title | Vision-based Pedestrian Protection Systems for Intelligent Vehicles | Type | Book Whole | ||
Year | 2014 | Publication | SpringerBriefs in Computer Science | Abbreviated Journal | |
Volume | Issue | Pages | 1-114 | ||
Keywords | Computer Vision; Driver Assistance Systems; Intelligent Vehicles; Pedestrian Detection; Vulnerable Road Users | ||||
Abstract | Pedestrian Protection Systems (PPSs) are on-board systems aimed at detecting and tracking people in the surroundings of a vehicle in order to avoid potentially dangerous situations. These systems, together with other Advanced Driver Assistance Systems (ADAS) such as lane departure warning or adaptive cruise control, are one of the most promising ways to improve traffic safety. By the use of computer vision, cameras working either in the visible or infra-red spectra have been demonstrated as a reliable sensor to perform this task. Nevertheless, the variability of human’s appearance, not only in terms of clothing and sizes but also as a result of their dynamic shape, makes pedestrians one of the most complex classes even for computer vision. Moreover, the unstructured changing and unpredictable environment in which such on-board systems must work makes detection a difficult task to be carried out with the demanded robustness. In this brief, the state of the art in PPSs is introduced through the review of the most relevant papers of the last decade. A common computational architecture is presented as a framework to organize each method according to its main contribution. More than 300 papers are referenced, most of them addressing pedestrian detection and others corresponding to the descriptors (features), pedestrian models, and learning machines used. In addition, an overview of topics such as real-time aspects, systems benchmarking and future challenges of this research area are presented. | ||||
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Publisher | Springer Briefs in Computer Vision | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4614-7986-4 | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | GeL2014 | Serial | 2325 | ||
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Author | Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny | ||||
Title | Notation-invariant patch-based wall detector in architectural floor plans | Type | Book Chapter | ||
Year | 2013 | Publication | Graphics Recognition. New Trends and Challenges | Abbreviated Journal | |
Volume | 7423 | Issue | Pages | 79--88 | |
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Abstract | Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper. | ||||
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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 | 978-3-642-36823-3 | Medium | |
Area | Expedition | Conference | |||
Notes | DAG; 600.045; 600.056; 605.203 | Approved | no | ||
Call Number | Admin @ si @ HMS2013 | Serial | 2322 | ||
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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 |
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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. | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 0018-9162 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | LAMP; | Approved | no | ||
Call Number | Admin @ si @ TSR2014a | Serial | 2317 | ||
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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 |
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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. | ||||
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Notes | LAMP; | 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. |
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Publisher | Elsevier | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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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 |
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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. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ GFV2013 | Serial | 2307 | ||
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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. | ||||
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Notes | DAG; 600.077; 602.101 | Approved | no | ||
Call Number | Admin @ si @ FFB2014 | Serial | 2297 | ||
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