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Author Marçal Rusiñol; Josep Llados
Title The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 55-60
Keywords
Abstract In this paper we present the importance of including the user in the loop in a 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 a baseline word spotting approach based on a bag-of-visual-words model.
Address (up) Bari, Italy
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 Admin @ si @ RuL2012 Serial 2054
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Author Volkmar Frinken; Markus Baumgartner; Andreas Fischer; Horst Bunke
Title Semi-Supervised Learning for Cursive Handwriting Recognition using Keyword Spotting Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 49-54
Keywords
Abstract State-of-the-art handwriting recognition systems are learning-based systems that require large sets of training data. The creation of training data, and consequently the creation of a well-performing recognition system, requires therefore a substantial amount of human work. This can be reduced with semi-supervised learning, which uses unlabeled text lines for training as well. Current approaches estimate the correct transcription of the unlabeled data via handwriting recognition which is not only extremely demanding as far as computational costs are concerned but also requires a good model of the target language. In this paper, we propose a different approach that makes use of keyword spotting, which is significantly faster and does not need any language model. In a set of experiments we demonstrate its superiority over existing approaches.
Address (up) Bari, Italy
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 10.1109/ICFHR.2012.268 ISBN 978-1-4673-2262-1 Medium
Area Expedition Conference ICFHR
Notes DAG Approved no
Call Number Admin @ si @ FBF2012 Serial 2055
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Author Emanuel Indermühle; Volkmar Frinken; Horst Bunke
Title Mode Detection in Online Handwritten Documents using BLSTM Neural Networks Type Conference Article
Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal
Volume Issue Pages 302-307
Keywords
Abstract Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data.
Address (up) Bari, italy
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 Admin @ si @ IFB2012 Serial 2056
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Author Ignasi Rius; Dani Rowe; Jordi Gonzalez; Xavier Roca
Title 3D Action Modeling and Reconstruction for 2D Human Body Tracking Type Miscellaneous
Year 2005 Publication 3rd International Conference on Advances in Pattern Recognition (ICAPR’2005), Pattern Recognition and Image Analysis, LNCS 3687: 146–154, ISBN 978–3–540–28833–6 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Bath (United Kingdom)
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
Notes ISE Approved no
Call Number ISE @ ise @ RRG2005c Serial 578
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Author Dani Rowe; Ignasi Rius; Jordi Gonzalez; Juan J. Villanueva
Title Improving Tracking by Handling Occlusions Type Miscellaneous
Year 2005 Publication 3rd International Conference on Advances in Pattern Recognition (ICAPR’2005), Pattern Recognition and Image Analysis, LNCS 3687: 146–154, ISBN 978–3–540–28833–6 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Bath (United Kingdom)
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
Notes Approved no
Call Number ISE @ ise @ RRG2005d Serial 619
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Author Quan-sen Sun; Zhong Jin; Pheng-ann Heng; De-shen Xia
Title A novel feature fusion method based on partial least squares regression Type Book Chapter
Year 2005 Publication Pattern Recognition and Data Mining, Lecture Notes in Computer Science, 3686: 268–277 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Bath (United Kingdom)
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
Notes Approved no
Call Number Admin @ si @ SJH2005 Serial 626
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Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
Title Wall Patch-Based Segmentation in Architectural Floorplans Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 1270-1274
Keywords
Abstract Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates.
Address (up) Beiging, China
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 1520-5363 ISBN 978-0-7695-4520-2 Medium
Area Expedition Conference ICDAR
Notes DAG Approved no
Call Number Admin @ si @ HMS2011a Serial 1792
Permanent link to this record
 
 
Author Fadi Dornaika; Angel Sappa
Title Appearance-based 3D Face Tracker: An Evaluation Study Type Miscellaneous
Year 2005 Publication 2nd IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance, 121–128 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Beijing (China)
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
Notes ADAS Approved no
Call Number ADAS @ adas @ DoS2005b Serial 580
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Author Fadi Dornaika; Franck Davoine
Title Simultaneous Facial Action Tracking and Expression Recognition using a Particle Filter Type Miscellaneous
Year 2005 Publication 10th IEEE Int. Conference on Computer Vision (ICCV) Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Beijing (China)
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
Notes Approved no
Call Number Admin @ si @ DoD2005d Serial 581
Permanent link to this record
 
 
Author Zhong Jin; Jing-Yu Yang; Zhen Lou
Title A luminance-conditional distribution model of skin color information Type Miscellaneous
Year 2005 Publication 2005 Beijing International Conference on Imaging: Technology and Applications for the 21th Century, 280–281 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address (up) Beijing (China)
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
Notes Approved no
Call Number Admin @ si @ JYL2005 Serial 628
Permanent link to this record
 
 
Author Sergio Escalera; Petia Radeva; Jordi Vitria; Xavier Baro; Bogdan Raducanu
Title Modelling and Analyzing Multimodal Dyadic Interactions Using Social Networks Type Conference Article
Year 2010 Publication 12th International Conference on Multimodal Interfaces and 7th Workshop on Machine Learning for Multimodal Interaction. Abbreviated Journal
Volume Issue Pages
Keywords Social interaction; Multimodal fusion, Influence model; Social network analysis
Abstract Social network analysis became a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from
multimodal dyadic interactions. First, speech detection is performed through an audio/visual fusion scheme based on stacked sequential learning. In the audio domain, speech is detected through clusterization of audio features. Clusters
are modelled by means of an One-state Hidden Markov Model containing a diagonal covariance Gaussian Mixture Model. In the visual domain, speech detection is performed through differential-based feature extraction from the segmented
mouth region, and a dynamic programming matching procedure. Second, in order to model the dyadic interactions, we employed the Influence Model whose states
encode the previous integrated audio/visual data. Third, the social network is extracted based on the estimated influences. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The results
are reported both in terms of accuracy of the audio/visual data fusion and centrality measures used to characterize the social network.
Address (up) Beijing (China)
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 ICMI-MLI
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ ERV2010 Serial 1427
Permanent link to this record
 
 
Author Aura Hernandez-Sabate; David Rotger; Debora Gil
Title Image-based ECG sampling of IVUS sequences Type Conference Article
Year 2008 Publication Proc. IEEE Ultrasonics Symp. IUS 2008 Abbreviated Journal
Volume Issue Pages 1330-1333
Keywords Longitudinal Motion; Image-based ECG-gating; Fourier analysis
Abstract Longitudinal motion artifacts in IntraVascular UltraSound (IVUS) sequences hinders a properly 3D reconstruction and vessel measurements. Most of current techniques base on the ECG signal to obtain a gated pullback without the longitudinal artifact by using a specific hardware or the ECG signal itself. The potential of IVUS images processing for phase retrieval still remains little explored. In this paper, we present a fast forward image-based algorithm to approach ECG sampling. Inspired on the fact that maximum and minimum lumen areas are related to end-systole and end-diastole, our cardiac phase retrieval is based on the analysis of tissue density of mass along the sequence. The comparison between automatic and manual phase retrieval (0.07 ± 0.07 mm. of error) encourages a deep validation contrasting with ECG signals.
Address (up) Beijing (China)
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
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ HRG2008 Serial 1553
Permanent link to this record
 
 
Author Jose Manuel Alvarez; Antonio Lopez
Title Novel Index for Objective Evaluation of Road Detection Algorithms Type Conference Article
Year 2008 Publication Intelligent Transportation Systems. 11th International IEEE Conference on, Abbreviated Journal
Volume Issue Pages 815–820
Keywords road detection
Abstract
Address (up) Beijing (Xina)
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 ITSC
Notes ADAS Approved no
Call Number ADAS @ adas @ AlL2008 Serial 1074
Permanent link to this record
 
 
Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados
Title Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 63-67
Keywords
Abstract In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts.
Address (up) Beijing, China
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 ICDAR
Notes DAG;ADAS Approved no
Call Number Admin @ si @ RAT2011 Serial 1788
Permanent link to this record
 
 
Author Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes
Title Co-training for Handwritten Word Recognition Type Conference Article
Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal
Volume Issue Pages 314-318
Keywords
Abstract To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition.
Address (up) Beijing, China
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 ICDAR
Notes DAG Approved no
Call Number Admin @ si @ FFB2011 Serial 1789
Permanent link to this record