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Author Jaume Gibert; Ernest Valveny
Title Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. Type Conference Article
Year 2010 Publication 13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition Abbreviated Journal
Volume 6218 Issue Pages 223–232
Keywords
Abstract Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster.
Address
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano,
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-14979-5 Medium
Area Expedition Conference S+SSPR
Notes DAG Approved no
Call Number DAG @ dag @ GiV2010 Serial 1416
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Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva
Title Recursive Coarse-to-Fine Localization for fast Object Recognition Type Conference Article
Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal
Volume 6313 Issue II Pages 280–293
Keywords
Abstract Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter.
Address Crete (Greece)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-15566-6 Medium
Area Expedition Conference ECCV
Notes ISE Approved no
Call Number DAG @ dag @ PGB2010 Serial 1438
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Author Carles Fernandez; Jordi Gonzalez; Xavier Roca
Title Automatic Learning of Background Semantics in Generic Surveilled Scenes Type Conference Article
Year 2010 Publication 11th European Conference on Computer Vision Abbreviated Journal
Volume 6313 Issue II Pages 678–692
Keywords
Abstract Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis.
Address Crete (Greece)
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-15551-2 Medium
Area Expedition Conference ECCV
Notes ISE Approved no
Call Number ISE @ ise @ FGR2010 Serial 1439
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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 (down) 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 Cesar Isaza; Joaquin Salas; Bogdan Raducanu
Title Toward the Detection of Urban Infrastructures Edge Shadows Type Conference Article
Year 2010 Publication 12th International Conference on Advanced Concepts for Intelligent Vision Systems Abbreviated Journal
Volume 6474 Issue I Pages 30–37
Keywords
Abstract In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising.
Address Sydney, Australia
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor eds. Blanc–Talon et al
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-17687-6 Medium
Area Expedition Conference ACIVS
Notes OR;MV Approved no
Call Number BCNPCL @ bcnpcl @ ISR2010 Serial 1458
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Author Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard
Title A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume 6388 Issue Pages 93–98
Keywords
Abstract We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.
Address
Corporate Author Thesis
Publisher Springer, Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-17710-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ LLR2010 Serial 1459
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Author Jaume Gibert; Ernest Valveny; Horst Bunke
Title Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis Type Conference Article
Year 2010 Publication 15th Iberoamerican Congress on Pattern Recognition Abbreviated Journal
Volume 6419 Issue Pages 30–37
Keywords
Abstract Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation.
Address Sao Paulo, Brazil
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-16686-0 Medium
Area Expedition Conference CIARP
Notes DAG Approved no
Call Number DAG @ dag @ GVB2010 Serial 1462
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Author Jaume Garcia; Debora Gil; Aura Hernandez-Sabate
Title Endowing Canonical Geometries to Cardiac Structures Type Book Chapter
Year 2010 Publication Statistical Atlases And Computational Models Of The Heart Abbreviated Journal
Volume 6364 Issue Pages 124-133
Keywords
Abstract International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
Address
Corporate Author Thesis
Publisher Springer Berlin / Heidelberg Place of Publication Editor Camara, O.; Pop, M.; Rhode, K.; Sermesant, M.; Smith, N.; Young, A.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ GGH2010b Serial 1515
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Author Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta
Title Structure-Preserving Smoothing of Biomedical Images Type Conference Article
Year 2009 Publication 13th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal
Volume 5702 Issue Pages 427-434
Keywords non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography.
Abstract Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images.
Address Münster, Germany
Corporate Author Thesis
Publisher Springer Berlin Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-03766-5 Medium
Area Expedition Conference CAIP
Notes IAM Approved no
Call Number IAM @ iam @ GHB2009 Serial 1527
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Author Debora Gil; Petia Radeva
Title Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling Type Book Chapter
Year 2003 Publication Energy Minimization Methods In Computer Vision And Pattern Recognition Abbreviated Journal LNCS
Volume 2683 Issue Pages 357-372
Keywords Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature
Abstract Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.
Address
Corporate Author Thesis
Publisher Springer, Berlin Place of Publication Lisbon, PORTUGAL Editor Springer, B.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 3-540-40498-8 Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GIR2003b Serial 1535
Permanent link to this record
 

 
Author Ole Vilhelm-Larsen; Petia Radeva; Enric Marti
Title Guidelines for choosing optimal parameters of elasticity for snakes Type Book Chapter
Year 1995 Publication Computer Analysis Of Images And Patterns Abbreviated Journal LNCS
Volume 970 Issue Pages 106-113
Keywords
Abstract This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes MILAB;IAM Approved no
Call Number IAM @ iam @ LRM1995b Serial 1558
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Author Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti
Title Symbol recognition: current advances and perspectives Type Book Chapter
Year 2002 Publication Graphics Recognition Algorithms And Applications Abbreviated Journal LNCS
Volume 2390 Issue Pages 104-128
Keywords
Abstract The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
Address London, UK
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor Dorothea Blostein and Young- Bin Kwon
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN 3-540-44066-6 Medium
Area Expedition Conference GREC
Notes DAG; IAM; Approved no
Call Number IAM @ iam @ LVS2002 Serial 1572
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Author Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil
Title Suppression of IVUS Image Rotation. A Kinematic Approach Type Book Chapter
Year 2005 Publication Functional Imaging and Modeling of the Heart Abbreviated Journal LNCS
Volume 3504 Issue Pages 889-892
Keywords
Abstract IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
Address
Corporate Author Thesis
Publisher Springer Berlin / Heidelberg Place of Publication Editor Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume 3504 Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RRR2005 Serial 1645
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Author Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie
Title Inferring the Performance of Medical Imaging Algorithms Type Conference Article
Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal
Volume 6854 Issue Pages 520-528
Keywords Validation, Statistical Inference, Medical Imaging Algorithms.
Abstract Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence.
Address Sevilla
Corporate Author Thesis
Publisher Springer-Verlag Berlin Heidelberg Place of Publication Berlin Editor Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch
Language Summary Language Original Title
Series Editor Series Title L Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CAIP
Notes IAM; ADAS Approved no
Call Number IAM @ iam @ HGR2011 Serial 1676
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Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño
Title A Region Segmentation Method for Colonoscopy Images Using a Model of Polyp Appearance Type Conference Article
Year 2011 Publication 5th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal
Volume 6669 Issue Pages 134-143   
Keywords Colonoscopy, Polyp Detection, Region Merging, Region Segmentation.
Abstract This work aims at the segmentation of colonoscopy images into a minimum number of informative regions. Our method performs in a way such, if a polyp is present in the image, it will be exclusively and totally contained in a single region. This result can be used in later stages to classify regions as polyp-containing candidates. The output of the algorithm also defines which regions can be considered as non-informative. The algorithm starts with a high number of initial regions and merges them taking into account the model of polyp appearance obtained from available data. The results show that our segmentations of polyp regions are more accurate than state-of-the-art methods.
Address Las Palmas de Gran Canaria, June 2011
Corporate Author SpringerLink Thesis
Publisher Place of Publication Editor Vitrià, Jordi and Sanches, João and Hernández, Mario
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title (down) LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-642-21256-7 Medium
Area 800 Expedition Conference IbPRIA
Notes MV;SIAI Approved no
Call Number IAM @ iam @ BSV2011c Serial 1696
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