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Author |
Bogdan Raducanu; Fadi Dornaika |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Appearance-based Face Recognition Using A Supervised Manifold Learning Framework |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Workshop on the Applications of Computer Vision |
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465-470 |
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Abstract |
Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance. |
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Breckenridge; CO; USA |
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IEEE Xplore |
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1550-5790 |
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978-1-4673-0233-3 |
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WACV |
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OR;MV |
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no |
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Admin @ si @ RaD2012d |
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1890 |
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Author |
Antonio Hernandez; Carlos Primo; Sergio Escalera |
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Title |
Automatic user interaction correction via Multi-label Graph cuts |
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Conference Article |
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Year |
2011 |
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In ICCV 2011 1st IEEE International Workshop on Human Interaction in Computer Vision HICV |
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1276-1281 |
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Abstract |
Most applications in image segmentation requires from user interaction in order to achieve accurate results. However, user wants to achieve the desired segmentation accuracy reducing effort of manual labelling. In this work, we extend standard multi-label α-expansion Graph Cut algorithm so that it analyzes the interaction of the user in order to modify the object model and improve final segmentation of objects. The approach is inspired in the fact that fast user interactions may introduce some pixel errors confusing object and background. Our results with different degrees of user interaction and input errors show high performance of the proposed approach on a multi-label human limb segmentation problem compared with classical α-expansion algorithm. |
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978-1-4673-0062-9 |
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HICV |
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MILAB; HuPBA |
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no |
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Admin @ si @ HPE2011 |
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1892 |
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Author |
Miguel Reyes; Gabriel Dominguez; Sergio Escalera |
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Title |
Feature Weighting in Dynamic Time Warping for Gesture Recognition in Depth Data |
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Conference Article |
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Year |
2011 |
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1st IEEE Workshop on Consumer Depth Cameras for Computer Vision |
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1182-1188 |
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Abstract |
We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability. Feature Weighting in Dynamic Time Warping is then applied for recognizing begin-end of gestures in data sequences. The obtained results recognizing several gestures in depth data show high performance compared with classical Dynamic Time Warping approach. |
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978-1-4673-0062-9 |
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CDC4CV |
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HuPBA;MILAB |
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Admin @ si @ RDE2011 |
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1893 |
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Author |
Santiago Segui; Michal Drozdzal; Petia Radeva; Jordi Vitria |
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Title |
An Integrated Approach to Contextual Face Detection |
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Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
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143-150 |
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Face detection is, in general, based on content-based detectors. Nevertheless, the face is a non-rigid object with well defined relations with respect to the human body parts. In this paper, we propose to take benefit of the context information in order to improve content-based face detections. We propose a novel framework for integrating multiple content- and context-based detectors in a discriminative way. Moreover, we develop an integrated scoring procedure that measures the ’faceness’ of each hypothesis and is used to discriminate the detection results. Our approach detects a higher rate of faces while minimizing the number of false detections, giving an average increase of more than 10% in average precision when comparing it to state-of-the art face detectors |
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Vilamoura, Algarve, Portugal |
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Springer |
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ICPRAM |
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MILAB; OR;MV |
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no |
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Admin @ si @ SDR2012 |
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1895 |
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Author |
Michal Drozdzal; Santiago Segui; Petia Radeva; Jordi Vitria; Laura Igual |
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Title |
System and Method for Displaying Motility Events in an in Vivo Image Stream |
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Patent |
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Year |
2011 |
Publication |
US 61/592,786 |
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Address |
Given Imaging |
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US Patent Office |
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MILAB; OR;MV |
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Admin @ si @ DSR2011 |
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1897 |
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Author |
Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil |
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Title |
Myocardial torsion estimation with Tagged-MRI in the OsiriX platform |
Type |
Conference Article |
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Year |
2012 |
Publication |
ISBI Workshop on Open Source Medical Image Analysis software |
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Abstract |
Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es |
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Barcelona, Spain |
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IEEE |
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Editor |
Wiro Niessen (Erasmus MC) and Marc Modat (UCL) |
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ISBI |
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IAM |
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no |
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IAM @ iam @ ACS2012 |
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1900 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
Type |
Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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Pages |
624-631 |
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Abstract |
Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Call Number |
Admin @ si @ MGH2013b |
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2351 |
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Permanent link to this record |
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Author |
Marco Pedersoli; Jordi Gonzalez; Xu Hu; Xavier Roca |
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Title |
Toward Real-Time Pedestrian Detection Based on a Deformable Template Model |
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Journal Article |
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Year |
2014 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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15 |
Issue |
1 |
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355-364 |
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Abstract |
Most advanced driving assistance systems already include pedestrian detection systems. Unfortunately, there is still a tradeoff between precision and real time. For a reliable detection, excellent precision-recall such a tradeoff is needed to detect as many pedestrians as possible while, at the same time, avoiding too many false alarms; in addition, a very fast computation is needed for fast reactions to dangerous situations. Recently, novel approaches based on deformable templates have been proposed since these show a reasonable detection performance although they are computationally too expensive for real-time performance. In this paper, we present a system for pedestrian detection based on a hierarchical multiresolution part-based model. The proposed system is able to achieve state-of-the-art detection accuracy due to the local deformations of the parts while exhibiting a speedup of more than one order of magnitude due to a fast coarse-to-fine inference technique. Moreover, our system explicitly infers the level of resolution available so that the detection of small examples is feasible with a very reduced computational cost. We conclude this contribution by presenting how a graphics processing unit-optimized implementation of our proposed system is suitable for real-time pedestrian detection in terms of both accuracy and speed. |
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1524-9050 |
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ISE; 601.213; 600.078 |
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PGH2014 |
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2350 |
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Author |
Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; J. Mauri; Petia Radeva |
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Title |
Learning to Detect Stent Struts in Intravascular Ultrasound |
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Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
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7887 |
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575-583 |
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In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% . |
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Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-38627-5 |
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IbPRIA |
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MILAB; HuPBA; 605.203; 600.046 |
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Admin @ si @ CHB2013 |
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2349 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Classification of Administrative Document Images by Logo Identification |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.056; 600.045; 605.203 |
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Admin @ si @ |
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2348 |
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Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
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Bethlehem; PA; USA; August 2013 |
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GREC |
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DAG; 600.045; 600.055; 600.061; 602.101 |
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Admin @ si @ RKL2013 |
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2347 |
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Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Field Extraction from Administrative Documents by Incremental Structural Templates |
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Conference Article |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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1100 - 1104 |
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In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; 600.56; 600.045; 605.203; 602.101 |
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no |
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Admin @ si @ RBP2013 |
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2346 |
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Author |
Albert Gordo; Marçal Rusiñol; Dimosthenis Karatzas; Andrew Bagdanov |
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Title |
Document Classification and Page Stream Segmentation for Digital Mailroom Applications |
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Conference Article |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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621-625 |
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Abstract |
In this paper we present a method for the segmentation of continuous page streams into multipage documents and the simultaneous classification of the resulting documents. We first present an approach to combine the multiple pages of a document into a single feature vector that represents the whole document. Despite its simplicity and low computational cost, the proposed representation yields results comparable to more complex methods in multipage document classification tasks. We then exploit this representation in the context of page stream segmentation. The most plausible segmentation of a page stream into a sequence of multipage documents is obtained by optimizing a statistical model that represents the probability of each segmented multipage document belonging to a particular class. Experimental results are reported on a large sample of real administrative multipage documents. |
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Washington; USA; August 2013 |
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1520-5363 |
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DAG; 600.056; 602.101 |
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Admin @ si @ GRK2013c |
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2345 |
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Author |
L. Rothacker; Marçal Rusiñol; G.A. Fink |
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Bag-of-Features HMMs for segmentation-free word spotting in handwritten documents |
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Conference Article |
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2013 |
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12th International Conference on Document Analysis and Recognition |
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1305 - 1309 |
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Recent HMM-based approaches to handwritten word spotting require large amounts of learning samples and mostly rely on a prior segmentation of the document. We propose to use Bag-of-Features HMMs in a patch-based segmentation-free framework that are estimated by a single sample. Bag-of-Features HMMs use statistics of local image feature representatives. Therefore they can be considered as a variant of discrete HMMs allowing to model the observation of a number of features at a point in time. The discrete nature enables us to estimate a query model with only a single example of the query provided by the user. This makes our method very flexible with respect to the availability of training data. Furthermore, we are able to outperform state-of-the-art results on the George Washington dataset. |
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Washington; USA; August 2013 |
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Admin @ si @ RRF2013 |
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2344 |
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Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol |
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Interactive Document Retrieval and Classification. |
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2013 |
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Multimodal Interaction in Image and Video Applications |
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48 |
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17-30 |
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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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Springer Berlin Heidelberg |
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Angel Sappa; Jordi Vitria |
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1868-4394 |
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978-3-642-35931-6 |
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Admin @ si @ VRM2013 |
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2341 |
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