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Author |
Jose Carlos Rubio |
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Title |
Graph matching based on graphical models with application to vehicle tracking and classification at night |
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Report |
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2009 |
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CVC Technical Report |
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144 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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CIC |
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no |
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Admin @ si @ Rub2009 |
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2398 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Automatic Interpretation of Proofreading Sketches |
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Miscellaneous |
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Year |
2006 |
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3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 35–42 |
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Vienna (Austria) |
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DAG |
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DAG @ dag @ RSL2006a |
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716 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Rejection strategies involving classifier combination for handwriting recognition |
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Book Chapter |
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Year |
2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:97–104 |
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Girona (Spain) |
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DAG |
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DAG @ dag @ RSL2007a |
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777 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
A Pen-based Interface for Real-time Document Edition |
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Conference Article |
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Year |
2007 |
Publication |
9th International Conference on Document Analysis and Recognition. |
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2 |
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939–944 |
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Curitiba (Brazil) |
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ICDAR |
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DAG |
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no |
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DAG @ dag @ RSL2007b |
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883 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Categorization of Digital Ink Elements using Spectral Features |
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Conference Article |
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Year |
2007 |
Publication |
Seventh IAPR International Workshop on Graphics Recognition |
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63–64 |
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Curitiba (Brazil) |
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GREC |
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DAG |
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no |
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DAG @ dag @ RSL2007c |
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888 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Categorization of Digital Ink Elements using Spectral Features |
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Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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5046 |
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188–198 |
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Springer–Verlag |
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W. Liu, J. Llados, J.M. Ogier |
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DAG |
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no |
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DAG @ dag @ RSL2008 |
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1099 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
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Title |
Unsupervised writer style adaptation for handwritten word spotting |
Type |
Conference Article |
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Year |
2008 |
Publication |
Pattern Recognition. 19th International Conference on, IBM Best Student Paper Award. |
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Tampa, USA |
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ICPR |
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DAG |
Approved |
no |
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DAG @ dag @ RPS2008 |
Serial |
1077 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
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Title |
Unsupervised writer adaptation of whole-word HMMs with application to word-spotting |
Type |
Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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31 |
Issue |
8 |
Pages |
742–749 |
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Keywords |
Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis |
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Abstract |
In this paper we propose a novel approach for writer adaptation in a handwritten word-spotting task. The method exploits the fact that the semi-continuous hidden Markov model separates the word model parameters into (i) a codebook of shapes and (ii) a set of word-specific parameters.
Our main contribution is to employ this property to derive writer-specific word models by statistically adapting an initial universal codebook to each document. This process is unsupervised and does not even require the appearance of the keyword(s) in the searched document. Experimental results show an increase in performance when this adaptation technique is applied. To the best of our knowledge, this is the first work dealing with adaptation for word-spotting. The preliminary version of this paper obtained an IBM Best Student Paper Award at the 19th International Conference on Pattern Recognition. |
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Elsevier |
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DAG |
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no |
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DAG @ dag @ RPS2010 |
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1290 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
Type |
Book Chapter |
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Year |
2008 |
Publication |
Graphics Recognition: Recent Advances and New Opportunities |
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5046 |
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188–198 |
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W. Liu, J. Llados, J.M. Ogier |
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no |
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Call Number |
Admin @ si @ RoP2008a |
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992 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Handwritten word-spotting using hidden Markov models and universal vocabularies |
Type |
Journal Article |
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Year |
2009 |
Publication |
Pattern Recognition |
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PR |
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42 |
Issue |
9 |
Pages |
2103-2116 |
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Keywords |
Word-spotting; Hidden Markov model; Score normalization; Universal vocabulary; Handwriting recognition |
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Abstract |
Handwritten word-spotting is traditionally viewed as an image matching task between one or multiple query word-images and a set of candidate word-images in a database. This is a typical instance of the query-by-example paradigm. In this article, we introduce a statistical framework for the word-spotting problem which employs hidden Markov models (HMMs) to model keywords and a Gaussian mixture model (GMM) for score normalization. We explore the use of two types of HMMs for the word modeling part: continuous HMMs (C-HMMs) and semi-continuous HMMs (SC-HMMs), i.e. HMMs with a shared set of Gaussians. We show on a challenging multi-writer corpus that the proposed statistical framework is always superior to a traditional matching system which uses dynamic time warping (DTW) for word-image distance computation. A very important finding is that the SC-HMM is superior when labeled training data is scarce—as low as one sample per keyword—thanks to the prior information which can be incorporated in the shared set of Gaussians. |
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Elsevier |
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0031-3203 |
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no |
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Admin @ si @ RoP2009 |
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1053 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents |
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Conference Article |
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Year |
2008 |
Publication |
International Conference on Frontiers in Handwriting Recognition |
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7–12 |
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Montreal (Canada) |
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ICFHR |
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no |
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Admin @ si @ RoP2008b |
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1066 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin |
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Title |
Score Normalization for Hmm-based Word Spotting Using Universal Background Model |
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Conference Article |
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2008 |
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International Conference on Frontiers in Handwriting Recognition |
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82–87 |
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Montreal (Canada) |
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ICFHR |
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no |
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Admin @ si @ RoP2008c |
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1067 |
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Author |
Jose Antonio Rodriguez |
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Title |
Pen-based Interfaces and Recognition: Application to Proofreading Interpretation |
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Report |
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2006 |
Publication |
CVC Technical Report #96 |
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CVC (UAB) |
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no |
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Admin @ si @ Rod2006 |
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669 |
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Author |
Jose Antonio Rodriguez |
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Title |
Statistical frameworks and prior information modeling in handwritten word-spotting |
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Book Whole |
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2009 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Handwritten word-spotting (HWS) is the pattern analysis task that consists in finding keywords in handwritten document images. So far, HWS has been applied mostly to historical documents in order to build search engines for such image collections. This thesis addresses the problem of word-spotting for detecting important keywords in business documents. This is a first step towards the process of automatic routing of correspondence based on content.
However, the application of traditional HWS techniques fails for this type of documents. As opposed to historical documents, real business documents present a very high variability in terms of writing styles, spontaneous writing, crossed-out words, spelling mistakes, etc. The main goal of this thesis is the development of pattern recognition techniques that lead to a high-performance HWS system for this challenging type of data.
We develop a statistical framework in which word models are expressed in terms of hidden Markov models and the a priori information is encoded in a universal vocabulary of Gaussian codewords. This systems leads to a very robust performance in word-spotting task. We also find that by constraining the word models to the universal vocabulary, the a priori information of the problem of interest can be exploited for developing new contributions. These include a novel writer adaptation method, a system for searching handwritten words by generating typed text images, and a novel model-based similarity between feature vector sequences. |
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Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Gemma Sanchez;Josep Llados;Florent Perronnin |
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no |
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Admin @ si @ Rod2009 |
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1266 |
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Author |
Jose A. Garcia; David Masip; Valerio Sbragaglia; Jacopo Aguzzi |
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Title |
Automated Identification and Tracking of Nephrops norvegicus (L.) Using Infrared and Monochromatic Blue Light |
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Conference Article |
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2016 |
Publication |
19th International Conference of the Catalan Association for Artificial Intelligence |
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computer vision; video analysis; object recognition; tracking; behaviour; social; decapod; Nephrops norvegicus |
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Automated video and image analysis can be a very efficient tool to analyze
animal behavior based on sociality, especially in hard access environments
for researchers. The understanding of this social behavior can play a key role in the sustainable design of capture policies of many species. This paper proposes the use of computer vision algorithms to identify and track a specific specie, the Norway lobster, Nephrops norvegicus, a burrowing decapod with relevant commercial value which is captured by trawling. These animals can only be captured when are engaged in seabed excursions, which are strongly related with their social behavior.
This emergent behavior is modulated by the day-night cycle, but their social
interactions remain unknown to the scientific community. The paper introduces an identification scheme made of four distinguishable black and white tags (geometric shapes). The project has recorded 15-day experiments in laboratory pools, under monochromatic blue light (472 nm.) and darkness conditions (recorded using Infra Red light). Using this massive image set, we propose a comparative of state-ofthe-art computer vision algorithms to distinguish and track the different animals’ movements. We evaluate the robustness to the high noise presence in the infrared video signals and free out-of-plane rotations due to animal movement. The experiments show promising accuracies under a cross-validation protocol, being adaptable to the automation and analysis of large scale data. In a second contribution, we created an extensive dataset of shapes (46027 different shapes) from four daily experimental video recordings, which will be available to the community. |
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Barcelona; Spain; October 2016 |
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CCIA |
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OR;MV; |
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Admin @ si @ GMS2016 |
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2816 |
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