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Author |
Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva |
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Title |
With whom do I interact with? Social interaction detection in egocentric photo-streams |
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Conference Article |
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Year |
2016 |
Publication |
23rd International Conference on Pattern Recognition |
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Given a user wearing a low frame rate wearable camera during a day, this work aims to automatically detect the moments when the user gets engaged into a social interaction solely by reviewing the automatically captured photos by the worn camera. The proposed method, inspired by the sociological concept of F-formation, exploits distance and orientation of the appearing individuals -with respect to the user- in the scene from a bird-view perspective. As a result, the interaction pattern over the sequence can be understood as a two-dimensional time series that corresponds to the temporal evolution of the distance and orientation features over time. A Long-Short Term Memory-based Recurrent Neural Network is then trained to classify each time series. Experimental evaluation over a dataset of 30.000 images has shown promising results on the proposed method for social interaction detection in egocentric photo-streams. |
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Cancun; Mexico; December 2016 |
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ICPR |
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MILAB |
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no |
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Admin @ si @ADR2016a |
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2791 |
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Author |
Mariella Dimiccoli; Petia Radeva |
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Title |
Lifelogging in the era of outstanding digitization |
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2015 |
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International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage |
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In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. |
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Verliko Tarmovo; Bulgaria; September 2015 |
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DiPP |
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MILAB |
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no |
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Admin @ si @DiR2016 |
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2792 |
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Author |
Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer |
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Title |
UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images |
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2015 |
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2015 MediaEval Retrieving Diverse Images Task |
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This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. |
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Wurzen; Germany; September 2015 |
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MediaEval |
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MILAB |
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no |
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Admin @ si @LGB2016 |
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2793 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Evaluating Color Representation for Online Road Detection |
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2013 |
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ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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594-595 |
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Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations. |
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CVVT:E2M |
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ADAS;ISE |
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no |
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Admin @ si @ AGL2013 |
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2794 |
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Author |
Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
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Title |
Dynamic Lexicon Generation for Natural Scene Images |
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Conference Article |
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Year |
2016 |
Publication |
14th European Conference on Computer Vision Workshops |
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395-410 |
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Keywords |
scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN |
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Abstract |
Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge bene t from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons
for scene images using only visual information. For this, we exploit
the correlation between visual and textual information in a dataset consisting
of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline. |
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Amsterdam; The Netherlands; October 2016 |
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ECCVW |
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DAG; 600.084 |
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Admin @ si @ PGR2016 |
Serial |
2825 |
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Author |
Dan Norton; Fernando Vilariño; Onur Ferhat |
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Title |
Memory Field – Creative Engagement in Digital Collections |
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Conference Article |
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Year |
2015 |
Publication |
Internet Librarian International Conference |
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“Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields). |
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London; UK; October 2015 |
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ILI |
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MV;SIAI |
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no |
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Call Number |
Admin @ si @NVF2015 |
Serial |
2796 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas |
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Title |
The Library Living Lab |
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Conference Article |
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Year |
2015 |
Publication |
Open Living Lab Days |
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Address |
Istanbul; Turkey; August 2015 |
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OLLD |
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MV; DAG;SIAI |
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no |
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Admin @ si @ViK2015 |
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2797 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel |
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Title |
An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres |
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2015 |
Publication |
The White Book on Public Library Network from Diputació de Barcelona |
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MV; DAG;SIAI |
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Admin @ si @VKC2015 |
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2798 |
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Author |
Fernando Vilariño |
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Title |
Computer Vision and Performing Arts |
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2015 |
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Korean Scholars of Marketing Science |
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Seoul; Korea; October 2015 |
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KAMS |
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MV;SIAI |
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Admin @ si @Vil2015 |
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2799 |
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Author |
Fernando Vilariño; Dan Norton; Onur Ferhat |
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Title |
Memory Fields: DJs in the Library |
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2015 |
Publication |
21 st Symposium of Electronic Arts |
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Vancouver; Canada; August 2015 |
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ISEA |
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;SIAI |
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no |
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Admin @ si @VNF2015 |
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2800 |
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Author |
Fernando Vilariño; Dan Norton; Onur Ferhat |
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Title |
The Eye Doesn't Click – Eyetracking and Digital Content Interaction |
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2016 |
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4S/EASST Conference |
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Barcelona; Spain; September 2016 |
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EASST |
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MV; 600.097;SIAI |
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Admin @ si @VNF2016 |
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2801 |
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Author |
Fernando Vilariño |
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Title |
Giving Value to digital collections in the Public Library |
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2016 |
Publication |
Librarian 2020 |
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Brussels; Belgium; October 2016 |
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LIB |
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MV; 600.097;SIAI |
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Admin @ si @Vil2016a |
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2802 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas |
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Title |
A Living Lab approach for Citizen Science in Libraries |
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2016 |
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1st International ECSA Conference |
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Berlin; Germany; May 2016 |
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ECSA |
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MV; DAG; 600.084; 600.097;SIAI |
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Admin @ si @ViK2016 |
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2804 |
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Author |
Fernando Vilariño |
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Title |
Dissemination, creation and education from archives: Case study of the collection of Digitized Visual Poems from Joan Brossa Foundation |
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2016 |
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International Workshop on Poetry: Archives, Poetries and Receptions |
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Barcelona; Spain; October 2016 |
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POETRY |
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MV; 600.097;SIAI |
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no |
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Admin @ si @Vil2016b |
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2805 |
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Author |
Victor Ponce |
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Title |
Evolutionary Bags of Space-Time Features for Human Analysis |
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Book Whole |
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2016 |
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PhD Thesis Universitat de Barcelona, UOC and CVC |
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Computer algorithms; Digital image processing; Digital video; Analysis of variance; Dynamic programming; Evolutionary computation; Gesture |
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Abstract |
The representation (or feature) learning has been an emerging concept in the last years, since it collects a set of techniques that are present in any theoretical or practical methodology referring to artificial intelligence. In computer vision, a very common representation has adopted the form of the well-known Bag of Visual Words. This representation appears implicitly in most approaches where images are described, and is also present in a huge number of areas and domains: image content retrieval, pedestrian detection, human-computer interaction, surveillance, e-health, and social computing, amongst others. The early stages of this dissertation provide an approach for learning visual representations inside evolutionary algorithms, which consists of evolving weighting schemes to improve the BoVW representations for the task of recognizing categories of videos and images. Thus, we demonstrate the applicability of the most common weighting schemes, which are often used in text mining but are less frequently found in computer vision tasks. Beyond learning these visual representations, we provide an approach based on fusion strategies for learning spatiotemporal representations, from multimodal data obtained by depth sensors. Besides, we specially aim at the evolutionary and dynamic modelling, where the temporal factor is present in the nature of the data, such as video sequences of gestures and actions. Indeed, we explore the effects of probabilistic modelling for those approaches based on dynamic programming, so as to handle the temporal deformation and variance amongst video sequences of different categories. Finally, we integrate dynamic programming and generative models into an evolutionary computation framework, with the aim of learning Bags of SubGestures (BoSG) representations and hence to improve the generalization capability of standard gesture recognition approaches. The results obtained in the experimentation demonstrate, first, that evolutionary algorithms are useful for improving the representation of BoVW approaches in several datasets for recognizing categories in still images and video sequences. On the other hand, our experimentation reveals that both, the use of dynamic programming and generative models to align video sequences, and the representations obtained from applying fusion strategies in multimodal data, entail an enhancement on the performance when recognizing some gesture categories. Furthermore, the combination of evolutionary algorithms with models based on dynamic programming and generative approaches results, when aiming at the classification of video categories on large video datasets, in a considerable improvement over standard gesture and action recognition approaches. Finally, we demonstrate the applications of these representations in several domains for human analysis: classification of images where humans may be present, action and gesture recognition for general applications, and in particular for conversational settings within the field of restorative justice |
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June 2016 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Sergio Escalera;Xavier Baro;Hugo Jair Escalante |
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HuPBA |
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Pon2016 |
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2814 |
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