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	Author	E. Serradell; Adriana Romero; R. Leta; Carlo Gatta; Francesc Moreno-Noguer
	Title	Simultaneous Correspondence and Non-Rigid 3D Reconstruction of the Coronary Tree from Single X-Ray Images			Type	Conference Article
	Year	2011	Publication	13th IEEE International Conference on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	850-857
	Keywords
	Abstract
	Address	Barcelona
	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	ICCV
	Notes	MILAB			Approved	no
	Call Number	Admin @ si @ SRL2011			Serial	1803
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	Author	Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal
	Title	Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents			Type	Conference Article
	Year	2013	Publication	12th International Conference on Document Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	1078-1082
	Keywords
	Abstract	This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efﬁcient and natural way of representing graphical information with a graph but this is limited to cases where the information is well deﬁned with perfectly delineated regions. What if the information we are interested in is not conﬁned within well deﬁned regions? This paper addresses this particular problem and solves it by deﬁning near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efﬁciently. Hence to solve this problem we have deﬁned a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after ﬁnding a key node in the input or target graph and iteratively identiﬁes similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artiﬁcial, real and distorted datasets.
	Address	Washington; USA; August 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	1520-5363	ISBN		Medium
	Area		Expedition		Conference	ICDAR
	Notes	DAG; 600.045; 600.056; 600.061; 601.152			Approved	no
	Call Number	Admin @ si @ DLB2013a			Serial	2358
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	Author	Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal
	Title	A Product graph based method for dual subgraph matching applied to symbol spotting			Type	Conference Article
	Year	2013	Publication	10th IAPR International Workshop on Graphics Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Product graph has been shown to be an efﬁcient way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. This paper focuses on the two major limitations of the previous version of product graph: (1) Spurious nodes and edges in the graph representation and (2) Inefﬁcient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual graph representation on the original graph representing the graphical information and the product graph is computed between the dual graphs of the query graphs and the input graph. The dual graph with redundant edges is helpful for efﬁcient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates similar path information of two graphs and exponentiating the adjacency matrix ﬁnds similar paths of greater lengths. Nodes joining similar paths between two graphs are found by combining different exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.
	Address	Bethlehem; PA; USA; August 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	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DLB2013b			Serial	2359
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	Author	Nataliya Shapovalova; Carles Fernandez; Xavier Roca; Jordi Gonzalez
	Title	Semantics of Human Behavior in Image Sequences			Type	Book Chapter
	Year	2011	Publication	Computer Analysis of Human Behavior	Abbreviated Journal
	Volume		Issue	7	Pages	151-182
	Keywords
	Abstract	Human behavior is contextualized and understanding the scene of an action is crucial for giving proper semantics to behavior. In this chapter we present a novel approach for scene understanding. The emphasis of this work is on the particular case of Human Event Understanding. We introduce a new taxonomy to organize the different semantic levels of the Human Event Understanding framework proposed. Such a framework particularly contributes to the scene understanding domain by (i) extracting behavioral patterns from the integrative analysis of spatial, temporal, and contextual evidence and (ii) integrative analysis of bottom-up and top-down approaches in Human Event Understanding. We will explore how the information about interactions between humans and their environment influences the performance of activity recognition, and how this can be extrapolated to the temporal domain in order to extract higher inferences from human events observed in sequences of images.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor	Albert Ali Salah;
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-85729-993-2	Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ SFR2011			Serial	1810
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	Author	Bhaskar Chakraborty; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez; Xavier Roca
	Title	A Selective Spatio-Temporal Interest Point Detector for Human Action Recognition in Complex Scenes			Type	Conference Article
	Year	2011	Publication	13th IEEE International Conference on Computer Vision	Abbreviated Journal
	Volume		Issue		Pages	1776-1783
	Keywords
	Abstract	Recent progress in the field of human action recognition points towards the use of Spatio-Temporal Interest Points (STIPs) for local descriptor-based recognition strategies. In this paper we present a new approach for STIP detection by applying surround suppression combined with local and temporal constraints. Our method is significantly different from existing STIP detectors and improves the performance by detecting more repeatable, stable and distinctive STIPs for human actors, while suppressing unwanted background STIPs. For action representation we use a bag-of-visual words (BoV) model of local N-jet features to build a vocabulary of visual-words. To this end, we introduce a novel vocabulary building strategy by combining spatial pyramid and vocabulary compression techniques, resulting in improved performance and efficiency. Action class specific Support Vector Machine (SVM) classifiers are trained for categorization of human actions. A comprehensive set of experiments on existing benchmark datasets, and more challenging datasets of complex scenes, validate our approach and show state-of-the-art performance.
	Address	Barcelona
	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	1550-5499	ISBN	978-1-4577-1101-5	Medium
	Area		Expedition		Conference	ICCV
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ CHM2011			Serial	1811
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	Author	Wenjuan Gong; Jürgen Brauer; Michael Arens; Jordi Gonzalez
	Title	Modeling vs. Learning Approaches for Monocular 3D Human Pose Estimation			Type	Conference Article
	Year	2011	Publication	1st IEEE International Workshop on Performance Evaluation on Recognition of Human Actions and Pose Estimation Methods	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	London, United Kingdom
	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	PERHAPS
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ GBA2011			Serial	1812
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	Author	Jordi Gonzalez; Josep M. Gonfaus; Carles Fernandez; Xavier Roca
	Title	Exploiting Natural-Language Interaction in Video Surveillance Systems			Type	Conference Article
	Year	2011	Publication	V&L Net Workshop on Vision and Language	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Brighton, UK
	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	VL
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ GGF2011			Serial	1813
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	Author	Murad Al Haj; Carles Fernandez; Zhanwu Xiong; Ivan Huerta; Jordi Gonzalez; Xavier Roca
	Title	Beyond the Static Camera: Issues and Trends in Active Vision			Type	Book Chapter
	Year	2011	Publication	Visual Analysis of Humans: Looking at People	Abbreviated Journal
	Volume		Issue	2	Pages	11-30
	Keywords
	Abstract	Maximizing both the area coverage and the resolution per target is highly desirable in many applications of computer vision. However, with a limited number of cameras viewing a scene, the two objectives are contradictory. This chapter is dedicated to active vision systems, trying to achieve a trade-off between these two aims and examining the use of high-level reasoning in such scenarios. The chapter starts by introducing different approaches to active cameras configurations. Later, a single active camera system to track a moving object is developed, offering the reader first-hand understanding of the issues involved. Another section discusses practical considerations in building an active vision platform, taking as an example a multi-camera system developed for a European project. The last section of the chapter reflects upon the future trends of using semantic factors to drive smartly coordinated active systems.
	Address
	Corporate Author				Thesis
	Publisher	Springer London	Place of Publication		Editor	Th.B. Moeslund; A. Hilton; V. Krüger; L. Sigal
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-0-85729-996-3	Medium
	Area		Expedition		Conference
	Notes	ISE			Approved	no
	Call Number	Admin @ si @ AFX2011			Serial	1814
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	Author	Albert Gordo; Florent Perronnin
	Title	Asymmetric Distances for Binary Embeddings			Type	Conference Article
	Year	2011	Publication	IEEE Conference on Computer Vision and Pattern Recognition	Abbreviated Journal
	Volume		Issue		Pages	729 - 736
	Keywords
	Abstract	In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH) and Semi-Supervised Hashing (SSH). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. We also propose a novel simple binary embedding technique – PCA Embedding (PCAE) – which is shown to yield competitive results with respect to more complex algorithms such as SH and SSH.
	Address	Providence, RI
	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	978-1-4577-0394-2	Medium
	Area		Expedition		Conference	CVPR
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ GoP2011; IAM @ iam @ GoP2011			Serial	1817
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	Author	Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
	Title	Descriptor-based Svm Wall Detector			Type	Conference Article
	Year	2011	Publication	9th International Workshop on Graphic Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach.
	Address
	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	Admin @ si @ HMS2011b			Serial	1819
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	Author	Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados
	Title	Classification of Administrative Document Images by Logo Identification			Type	Conference Article
	Year	2011	Publication	In proceedings of 9th IAPR Workshop on Graphic Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	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.
	Address	Seoul, Corea
	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	Admin @ si @ RPK2011			Serial	1821
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	Author	Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke
	Title	A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors			Type	Conference Article
	Year	2011	Publication	Proceedings of the 2011 Workshop on Historical Document Imaging and Processing	Abbreviated Journal
	Volume		Issue		Pages	83-90
	Keywords
	Abstract	The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach.
	Address
	Corporate Author				Thesis
	Publisher	ACM	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-4503-0916-5	Medium
	Area		Expedition		Conference	HIP
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ FFF2011a			Serial	1823
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	Author	Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke
	Title	Transcription Alignment of Latin Manuscripts Using Hidden Markov Models			Type	Conference Article
	Year	2011	Publication	Proceedings of the 2011 Workshop on Historical Document Imaging and Processing	Abbreviated Journal
	Volume		Issue		Pages	29-36
	Keywords
	Abstract	Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models.
	Address
	Corporate Author				Thesis
	Publisher	ACM	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	HIP
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ FFF2011b			Serial	1824
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	Author	Anjan Dutta; Josep Llados; Umapada Pal
	Title	Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings			Type	Conference Article
	Year	2011	Publication	In proceedings of 9th IAPR Workshop on Graphic Recognition	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words.
	Address	Seoul, Korea
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-36823-3	Medium
	Area		Expedition		Conference	GREC
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ DLP2011c			Serial	1825
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	Author	Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke
	Title	Writer Identification in Old Handwritten Music Scores			Type	Book Chapter
	Year	2012	Publication	Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology	Abbreviated Journal
	Volume		Issue		Pages	27-63
	Keywords
	Abstract	The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%.
	Address
	Corporate Author				Thesis
	Publisher	IGI-Global	Place of Publication		Editor	Copnstantin Papaodysseus
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ FLS2012			Serial	1828
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