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	Author	Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds)
	Title	Graphics Recognition: Achievements, Challenges, and Evolution			Type	Book Whole
	Year	2010	Publication	8th International Workshop GREC 2009.	Abbreviated Journal
	Volume	6020	Issue		Pages
	Keywords
	Abstract
	Address	La Rochelle
	Corporate Author				Thesis
	Publisher	Springer Link	Place of Publication		Editor	Jean-Marc Ogier; Wenyin Liu; Josep Llados
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ OLL2010			Serial	1976
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	Author	Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke
	Title	Symbol-independent writer identification in old handwritten music scores			Type	Conference Article
	Year	2009	Publication	In proceedings of 8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	186–197
	Keywords
	Abstract
	Address	La Rochelle, France
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ FLS2009a			Serial	1222
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	Author	Salim Jouili; Salvatore Tabbone; Ernest Valveny
	Title	Evaluation of graph matching measures for documents retrieval			Type	Conference Article
	Year	2009	Publication	In proceedings of 8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	13–21
	Keywords	Graph Matching; Graph retrieval; structural representation; Performance Evaluation
	Abstract	In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used which include line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each grahp distance measure depends on the kind of data and the graph representation technique.
	Address	La Rochelle, France
	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	0302-9743	ISBN	978-3-642-13727-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ JTV2009a			Serial	1230
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	Author	Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados
	Title	A Generic Image Retrieval Method for Date Estimation of Historical Document Collections			Type	Conference Article
	Year	2022	Publication	Document Analysis Systems.15th IAPR International Workshop, (DAS2022)	Abbreviated Journal
	Volume	13237	Issue		Pages	583–597
	Keywords	Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG
	Abstract	Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.
	Address	La Rochelle, France; May 22–25, 2022
	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	DAS
	Notes	DAG; 600.140; 600.121			Approved	no
	Call Number	Admin @ si @ MGR2022			Serial	3694
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	Author	Josep Brugues Pujolras; Lluis Gomez; Dimosthenis Karatzas
	Title	A Multilingual Approach to Scene Text Visual Question Answering			Type	Conference Article
	Year	2022	Publication	Document Analysis Systems.15th IAPR International Workshop, (DAS2022)	Abbreviated Journal
	Volume		Issue		Pages	65-79
	Keywords	Scene text; Visual question answering; Multilingual word embeddings; Vision and language; Deep learning
	Abstract	Scene Text Visual Question Answering (ST-VQA) has recently emerged as a hot research topic in Computer Vision. Current ST-VQA models have a big potential for many types of applications but lack the ability to perform well on more than one language at a time due to the lack of multilingual data, as well as the use of monolingual word embeddings for training. In this work, we explore the possibility to obtain bilingual and multilingual VQA models. In that regard, we use an already established VQA model that uses monolingual word embeddings as part of its pipeline and substitute them by FastText and BPEmb multilingual word embeddings that have been aligned to English. Our experiments demonstrate that it is possible to obtain bilingual and multilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines.
	Address	La Rochelle, France; May 22–25, 2022
	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	DAS
	Notes	DAG; 611.004; 600.155; 601.002			Approved	no
	Call Number	Admin @ si @ BGK2022b			Serial	3695
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	Author	Joan Mas; Gemma Sanchez; Josep Llados
	Title	SSP: Sketching slide Presentations, a Syntactic Approach			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide.
	Address	La Rochelle; France; July 2009
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ MSL2009a			Serial	1441
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	Author	Salim Jouili; Salvatore Tabbone; Ernest Valveny
	Title	Comparing Graph Similarity Measures for Graphical Recognition.			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique.
	Address	La Rochelle; France; July 2009
	Corporate Author				Thesis
	Publisher	Springer	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ JTV2009			Serial	1442
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	Author	Sergi Garcia Bordils; George Tom; Sangeeth Reddy; Minesh Mathew; Marçal Rusiñol; C.V. Jawahar; Dimosthenis Karatzas
	Title	Read While You Drive-Multilingual Text Tracking on the Road			Type	Conference Article
	Year	2022	Publication	15th IAPR International workshop on document analysis systems	Abbreviated Journal
	Volume	13237	Issue		Pages	756–770
	Keywords
	Abstract	Visual data obtained during driving scenarios usually contain large amounts of text that conveys semantic information necessary to analyse the urban environment and is integral to the traffic control plan. Yet, research on autonomous driving or driver assistance systems typically ignores this information. To advance research in this direction, we present RoadText-3K, a large driving video dataset with fully annotated text. RoadText-3K is three times bigger than its predecessor and contains data from varied geographical locations, unconstrained driving conditions and multiple languages and scripts. We offer a comprehensive analysis of tracking by detection and detection by tracking methods exploring the limits of state-of-the-art text detection. Finally, we propose a new end-to-end trainable tracking model that yields state-of-the-art results on this challenging dataset. Our experiments demonstrate the complexity and variability of RoadText-3K and establish a new, realistic benchmark for scene text tracking in the wild.
	Address	La Rochelle; France; May 2022
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-3-031-06554-5	Medium
	Area		Expedition		Conference	DAS
	Notes	DAG; 600.155; 611.022; 611.004			Approved	no
	Call Number	Admin @ si @ GTR2022			Serial	3783
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	Author	Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
	Title	A Performance Characterization Algorithm for Symbol Localization			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages	3-11
	Keywords
	Abstract	In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
	Address	La Rochelle; July 2009
	Corporate Author				Thesis
	Publisher	Springer	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ DRV2009			Serial	1443
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	Author	Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados
	Title	Symbol Recognition Using a Concept Lattice of Graphical Patterns			Type	Conference Article
	Year	2009	Publication	8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
	Address	La Rochelle; July 2009
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RBO2009			Serial	1444
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	Author	Partha Pratim Roy; Umapada Pal; Josep Llados
	Title	Touching Text Character Localization in Graphical Documents using SIFT			Type	Conference Article
	Year	2009	Publication	In proceedings 8th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult. Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches.
	Address	La rochelle; July 2009
	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	GREC
	Notes	DAG			Approved	no
	Call Number	DAG @ dag @ RPL2009c			Serial	1445
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	Author	Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera
	Title	Support Vector Machines with Time Series Distance Kernels for Action Classification			Type	Conference Article
	Year	2016	Publication	IEEE Winter Conference on Applications of Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1-7
	Keywords
	Abstract	Despite the outperformance of Support Vector Machine (SVM) on many practical classification problems, the algorithm is not directly applicable to multi-dimensional trajectories having different lengths. In this paper, a new class of SVM that is applicable to trajectory classification, such as action recognition, is developed by incorporating two efficient time-series distances measures into the kernel function. Dynamic Time Warping and Longest Common Subsequence distance measures along with their derivatives are employed as the SVM kernel. In addition, the pairwise proximity learning strategy is utilized in order to make use of non-positive semi-definite kernels in the SVM formulation. The proposed method is employed for a challenging classification problem: action recognition by depth cameras using only skeleton data; and evaluated on three benchmark action datasets. Experimental results demonstrate the outperformance of our methodology compared to the state-ofthe-art on the considered datasets.
	Address	Lake Placid; NY (USA); March 2016
	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	WACV
	Notes	HuPBA;MILAB;			Approved	no
	Call Number	Admin @ si @ BGE2016a			Serial	2773
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	Author	Jiaolong Xu; Sebastian Ramos; Xu Hu; David Vazquez; Antonio Lopez
	Title	Multi-task Bilinear Classifiers for Visual Domain Adaptation			Type	Conference Article
	Year	2013	Publication	Advances in Neural Information Processing Systems Workshop	Abbreviated Journal
	Volume		Issue		Pages
	Keywords	Domain Adaptation; Pedestrian Detection; ADAS
	Abstract	We propose a method that aims to lessen the significant accuracy degradation that a discriminative classifier can suffer when it is trained in a specific domain (source domain) and applied in a different one (target domain). The principal reason for this degradation is the discrepancies in the distribution of the features that feed the classifier in different domains. Therefore, we propose a domain adaptation method that maps the features from the different domains into a common subspace and learns a discriminative domain-invariant classifier within it. Our algorithm combines bilinear classifiers and multi-task learning for domain adaptation. The bilinear classifier encodes the feature transformation and classification parameters by a matrix decomposition. In this way, specific feature transformations for multiple domains and a shared classifier are jointly learned in a multi-task learning framework. Focusing on domain adaptation for visual object detection, we apply this method to the state-of-the-art deformable part-based model for cross domain pedestrian detection. Experimental results show that our method significantly avoids the domain drift and improves the accuracy when compared to several baselines.
	Address	Lake Tahoe; Nevada; USA; December 2013
	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	NIPSW
	Notes	ADAS; 600.054; 600.057; 601.217;ISE			Approved	no
	Call Number	ADAS @ adas @ XRH2013			Serial	2340
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	Author	Mohammad N. S. Jahromi; Morten Bojesen Bonderup; Maryam Asadi-Aghbolaghi; Egils Avots; Kamal Nasrollahi; Sergio Escalera; Shohreh Kasaei; Thomas B. Moeslund; Gholamreza Anbarjafari
	Title	Automatic Access Control Based on Face and Hand Biometrics in a Non-cooperative Context			Type	Conference Article
	Year	2018	Publication	IEEE Winter Applications of Computer Vision Workshops	Abbreviated Journal
	Volume		Issue		Pages	28-36
	Keywords	IEEE Winter Applications of Computer Vision Workshops
	Abstract	Automatic access control systems (ACS) based on the human biometrics or physical tokens are widely employed in public and private areas. Yet these systems, in their conventional forms, are restricted to active interaction from the users. In scenarios where users are not cooperating with the system, these systems are challenged. Failure in cooperation with the biometric systems might be intentional or because the users are incapable of handling the interaction procedure with the biometric system or simply forget to cooperate with it, due to for example, illness like dementia. This work introduces a challenging bimodal database, including face and hand information of the users when they approach a door to open it by its handle in a noncooperative context. We have defined two (an easy and a challenging) protocols on how to use the database. We have reported results on many baseline methods, including deep learning techniques as well as conventional methods on the database. The obtained results show the merit of the proposed database and the challenging nature of access control with non-cooperative users.
	Address	Lake Tahoe; USA; March 2018
	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	WACVW
	Notes	HUPBA; 602.133			Approved	no
	Call Number	Admin @ si @ JBA2018			Serial	3121
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	Author	Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez
	Title	Efficient On-Board Stereo Vision Pose Estimation			Type	Conference Article
	Year	2007	Publication	Computer Aided Systems Theory, Selected paper from	Abbreviated Journal
	Volume	4739	Issue		Pages	1183–1190
	Keywords
	Abstract	This paper presents an efficient technique for real time estimation of on-board stereo vision system pose. The whole process is performed in the Euclidean space and consists of two stages. Initially, a compact representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the 3D road points. Fast RANSAC fitting is obtained by selecting points according to a probability distribution function that takes into account the density of points at a given depth. Finally, stereo camera position and orientation—pose—is computed relative to the road plane. The proposed technique is intended to be used on driver assistance systems for applications such as obstacle or pedestrian detection. A real time performance is reached. Experimental results on several environments and comparisons with a previous work are presented.
	Address	Las Palmas de Gran Canaria (Spain)
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	EUROCAST
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ SDG2007b			Serial	916
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