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Joan Serrat; J. Argemi; Juan J. Villanueva |
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Title |
Automatization of TW2 method using a knowledge-based image analysis system. |
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Conference Article |
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1991 |
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VIth International Congress of Auxology. |
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Madrid |
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ADAS |
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ADAS @ adas @ SAV1991 |
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259 |
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Author |
Joan Serrat; Javier Varona; Antonio Lopez; Xavier Roca; Juan J. Villanueva |
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Title |
P3: a three-dimensional digitizer prototype. |
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Miscellaneous |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:315–322. |
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Castellon. |
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ADAS;ISE |
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ADAS @ adas @ SVL2001 |
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213 |
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Author |
Joan Serrat; Jordi Vitria; J. Pladellorens |
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Title |
Morphological Segmentation of Heart Scintigraphic image Sequences. |
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Conference Article |
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Year |
1991 |
Publication |
Computer Assisted Radiology. |
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Berlin |
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ADAS;OR;MV |
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ADAS @ adas @ SVP1991 |
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263 |
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Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Anna Cabre |
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Title |
Bridging the gap between historical demography and computing: tools for computer-assisted transcription and the analysis of demographic sources |
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Book Chapter |
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2016 |
Publication |
The future of historical demography. Upside down and inside out |
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127-131 |
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Acco Publishers |
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K.Matthijs; S.Hin; H.Matsuo; J.Kok |
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978-94-6292-722-3 |
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DAG; 600.097 |
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Admin @ si @ PFL2016 |
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2907 |
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Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Gabriel Brea-Martinez; Miquel Valls-Figols |
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Title |
The Baix Llobregat (BALL) Demographic Database, between Historical Demography and Computer Vision (nineteenth–twentieth centuries |
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Book Chapter |
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2019 |
Publication |
Nominative Data in Demographic Research in the East and the West: monograph |
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29-61 |
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The Baix Llobregat (BALL) Demographic Database is an ongoing database project containing individual census data from the Catalan region of Baix Llobregat (Spain) during the nineteenth and twentieth centuries. The BALL Database is built within the project ‘NETWORKS: Technology and citizen innovation for building historical social networks to understand the demographic past’ directed by Alícia Fornés from the Center for Computer Vision and Joana Maria Pujadas-Mora from the Center for Demographic Studies, both at the Universitat Autònoma de Barcelona, funded by the Recercaixa program (2017–2019).
Its webpage is http://dag.cvc.uab.es/xarxes/.The aim of the project is to develop technologies facilitating massive digitalization of demographic sources, and more specifically the padrones (local censuses), in order to reconstruct historical ‘social’ networks employing computer vision technology. Such virtual networks can be created thanks to the linkage of nominative records compiled in the local censuses across time and space. Thus, digitized versions of individual and family lifespans are established, and individuals and families can be located spatially. |
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978-5-7996-2656-3 |
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DAG; 600.121 |
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no |
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Admin @ si @ PFL2019 |
Serial |
3351 |
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Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Oriol Ramos Terrades; Josep Llados; Jialuo Chen; Miquel Valls-Figols; Anna Cabre |
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Title |
The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomic Data |
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Journal |
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2022 |
Publication |
Historical Life Course Studies |
Abbreviated Journal |
HLCS |
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12 |
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Pages |
99-132 |
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Keywords |
Individual demographic databases; Computer vision, Record linkage; Social mobility; Inequality; Migration; Word spotting; Handwriting recognition; Local censuses; Marriage Licences |
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Abstract |
The Barcelona Historical Marriage Database (BHMD) gathers records of the more than 600,000 marriages celebrated in the Diocese of Barcelona and their taxation registered in Barcelona Cathedral's so-called Marriage Licenses Books for the long period 1451–1905 and the BALL Demographic Database brings together the individual information recorded in the population registers, censuses and fiscal censuses of the main municipalities of the county of Baix Llobregat (Barcelona). In this ongoing collection 263,786 individual observations have been assembled, dating from the period between 1828 and 1965 by December 2020. The two databases started as part of different interdisciplinary research projects at the crossroads of Historical Demography and Computer Vision. Their construction uses artificial intelligence and computer vision methods as Handwriting Recognition to reduce the time of execution. However, its current state still requires some human intervention which explains the implemented crowdsourcing and game sourcing experiences. Moreover, knowledge graph techniques have allowed the application of advanced record linkage to link the same individuals and families across time and space. Moreover, we will discuss the main research lines using both databases developed so far in historical demography. |
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June 23, 2022 |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ PFR2022 |
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3737 |
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Author |
Joaquin Salas; P. Martinez; Jordi Gonzalez |
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Title |
Background Updating with the Use of Intrinsic Curves |
Type |
Book Chapter |
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Year |
2006 |
Publication |
International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 731–742, ISBN 978–3–540–44891–4 |
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no |
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ISE @ ise @ SMG2006 |
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768 |
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Author |
Joaquin Salas; Wendy Avalos; Rafael Castañeda; Mario Maya |
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Title |
A machine-vision system to measure the parameters describing the performance of a Foucault pendulum |
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Journal |
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Year |
2006 |
Publication |
Machine Vision and Applications |
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Volume |
17 |
Issue |
2 |
Pages |
133–138 |
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no |
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Admin @ si @ SAC2006 |
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644 |
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Author |
Joel Barajas |
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Title |
Spectral Rigid Registration of Medical Images: Application to Tagged MRI and IVUS |
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Report |
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2007 |
Publication |
CVC Technical Report #106 |
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CVC (UAB) |
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no |
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Admin @ si @ Bar2007 |
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821 |
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Author |
Joel Barajas; Jaume Garcia; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
Angle Images Using Gabor Filters in Cardiac Tagged MRI |
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Conference Article |
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Year |
2005 |
Publication |
Proceeding of the 2005 conference on Artificial Intelligence Research and Development |
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107-114 |
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Angle Images, Gabor Filters, Harp, Tagged Mri |
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Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results. |
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Amsterdam; The Netherlands |
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IOS Press |
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Amsterdam, The Netherlands |
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1-58603-560-6 |
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CAIRD |
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Notes |
IAM;MILAB |
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no |
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BCNPCL @ bcnpcl @ BGC2005; IAM @ iam |
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595 |
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Author |
Joel Barajas; Jaume Garcia; Karla Lizbeth Caballero; Francesc Carreras; Sandra Pujades; Petia Radeva |
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Title |
Correction of Misalignment Artifacts Among 2-D Cardiac MR Images in 3-D Space |
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Conference Article |
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2006 |
Publication |
1st International Wokshop on Computer Vision for Intravascular and Intracardiac Imaging (CVII’06) |
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3217 |
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114-121 |
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Cardiac Magnetic Resonance images offer the opportunity to study the heart in detail. One of the main issues in its modelling is to create an accurate 3-D reconstruction of the left ventricle from 2-D views. A first step to achieve this goal is the correct registration among the different image planes due to patient movements. In this article, we present an accurate method to correct displacement artifacts using the Normalized Mutual Information. Here, the image views are treated as planes in order to diminish the approximation error caused by the association of a certain thickness, and moved simultaneously to avoid any kind of bias in the alignment process. This method has been validated using real and syntectic plane displacements, yielding promising results. |
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Copenhagen (Denmark) |
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978-3-540-22977-3 |
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IAM;MILAB |
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no |
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IAM @ iam @ BGC2006 |
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1485 |
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Author |
Joel Barajas; Karla Lizbeth Caballero; Petia Radeva |
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Title |
Cardiac Phase Extraction in IVUS Sequences Using 1-D Gabor Filters |
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Conference Article |
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2007 |
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Engineering in Medicine and Biology Society, 29th Annual International Conference of the IEEE |
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343–36 |
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Lyon (France) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ BCR2007 |
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924 |
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Author |
Jon Almazan |
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
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Report |
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2010 |
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CVC Technical Report |
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163 |
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Master's thesis |
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Admin @ si @ Alm2010 |
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1354 |
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Author |
Jon Almazan |
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Title |
Learning to Represent Handwritten Shapes and Words for Matching and Recognition |
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Book Whole |
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2014 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Writing is one of the most important forms of communication and for centuries, handwriting had been the most reliable way to preserve knowledge. However, despite the recent development of printing houses and electronic devices, handwriting is still broadly used for taking notes, doing annotations, or sketching ideas.
Transferring the ability of understanding handwritten text or recognizing handwritten shapes to computers has been the goal of many researches due to its huge importance for many different fields. However, designing good representations to deal with handwritten shapes, e.g. symbols or words, is a very challenging problem due to the large variability of these kinds of shapes. One of the consequences of working with handwritten shapes is that we need representations to be robust, i.e., able to adapt to large intra-class variability. We need representations to be discriminative, i.e., able to learn what are the differences between classes. And, we need representations to be efficient, i.e., able to be rapidly computed and compared. Unfortunately, current techniques of handwritten shape representation for matching and recognition do not fulfill some or all of these requirements.
Through this thesis we focus on the problem of learning to represent handwritten shapes aimed at retrieval and recognition tasks. Concretely, on the first part of the thesis, we focus on the general problem of representing any kind of handwritten shape. We first present a novel shape descriptor based on a deformable grid that deals with large deformations by adapting to the shape and where the cells of the grid can be used to extract different features. Then, we propose to use this descriptor to learn statistical models, based on the Active Appearance Model, that jointly learns the variability in structure and texture of a given class. Then, on the second part, we focus on a concrete application, the problem of representing handwritten words, for the tasks of word spotting, where the goal is to find all instances of a query word in a dataset of images, and recognition. First, we address the segmentation-free problem and propose an unsupervised, sliding-window-based approach that achieves state-of- the-art results in two public datasets. Second, we address the more challenging multi-writer problem, where the variability in words exponentially increases. We describe an approach in which both word images and text strings are embedded in a common vectorial subspace, and where those that represent the same word are close together. This is achieved by a combination of label embedding and attributes learning, and a common subspace regression. This leads to a low-dimensional, unified representation of word images and strings, resulting in a method that allows one to perform either image and text searches, as well as image transcription, in a unified framework. We evaluate our methods on different public datasets of both handwritten documents and natural images showing results comparable or better than the state-of-the-art on spotting and recognition tasks. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Ernest Valveny;Alicia Fornes |
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DAG; 600.077 |
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no |
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Admin @ si @ Alm2014 |
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2572 |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
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Title |
A non-rigid appearance model for shape description and recognition |
Type |
Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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45 |
Issue |
9 |
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3105--3113 |
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Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition |
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Abstract |
In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. |
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0031-3203 |
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DAG |
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DAG @ dag @ AFV2012 |
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1982 |
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Permanent link to this record |