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Author Jaume Gibert; Ernest Valveny; Horst Bunke edit  doi
isbn  openurl
  Title Dimensionality Reduction for Graph of Words Embedding Type Conference Article
  Year 2011 Publication 8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition Abbreviated Journal  
  Volume (down) 6658 Issue Pages 22-31  
  Keywords  
  Abstract The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs.  
  Address Münster, Germany  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-20843-0 Medium  
  Area Expedition Conference GbRPR  
  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2011a Serial 1743  
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Author Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich edit   pdf
url  isbn
openurl 
  Title Perception Based Representations for Computational Colour Type Conference Article
  Year 2011 Publication 3rd International Workshop on Computational Color Imaging Abbreviated Journal  
  Volume (down) 6626 Issue Pages 16-30  
  Keywords colour perception, induction, naming, psychophysical data, saliency, segmentation  
  Abstract The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space.  
  Address Milan, Italy  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor Raimondo Schettini, Shoji Tominaga, Alain Trémeau  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-20403-6 Medium  
  Area Expedition Conference CCIW  
  Notes CIC Approved no  
  Call Number Admin @ si @ VMB2011 Serial 1733  
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Author Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados edit  doi
isbn  openurl
  Title Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval Type Conference Article
  Year 2011 Publication 33rd European Conference on Information Retrieval Abbreviated Journal  
  Volume (down) 6611 Issue Pages 314-325  
  Keywords  
  Abstract In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.  
  Address Dublin, Ireland  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Editor P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-20160-8 Medium  
  Area Expedition Conference ECIR  
  Notes DAG; RV;ADAS Approved no  
  Call Number Admin @ si @ RAK2011 Serial 1737  
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Author C. Isaza; Joaquin Salas; Bogdan Raducanu edit  doi
isbn  openurl
  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 (down) 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 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 Jaume Gibert; Ernest Valveny; Horst Bunke edit  url
doi  isbn
openurl 
  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 (down) 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 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  
Permanent link to this record
 

 
Author Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard edit  doi
isbn  openurl
  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 (down) 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 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  
Permanent link to this record
 

 
Author Jaume Garcia; Debora Gil; Aura Hernandez-Sabate edit   pdf
doi  openurl
  Title Endowing Canonical Geometries to Cardiac Structures Type Book Chapter
  Year 2010 Publication Statistical Atlases And Computational Models Of The Heart Abbreviated Journal  
  Volume (down) 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 LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGH2010b Serial 1515  
Permanent link to this record
 

 
Author Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva edit  doi
isbn  openurl
  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 (down) 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 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  
Permanent link to this record
 

 
Author Carles Fernandez; Jordi Gonzalez; Xavier Roca edit  doi
isbn  openurl
  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 (down) 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 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  
Permanent link to this record
 

 
Author Jaume Gibert; Ernest Valveny edit  doi
isbn  openurl
  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 (down) 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 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 Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez edit  doi
isbn  openurl
  Title Automatic Key Pose Selection for 3D Human Action Recognition Type Conference Article
  Year 2010 Publication 6th International Conference on Articulated Motion and Deformable Objects Abbreviated Journal  
  Volume (down) 6169 Issue Pages 290–299  
  Keywords  
  Abstract This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Verlag 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 978-3-642-14060-0 Medium  
  Area Expedition Conference AMDO  
  Notes ISE Approved no  
  Call Number DAG @ dag @ GBR2010 Serial 1317  
Permanent link to this record
 

 
Author Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu edit  doi
isbn  openurl
  Title 3D Texton Spaces for color-texture retrieval Type Conference Article
  Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume (down) 6111 Issue Pages 354–363  
  Keywords  
  Abstract Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor A.C. Campilho and M.S. Kamel  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-13771-6 Medium  
  Area Expedition Conference ICIAR  
  Notes CIC Approved no  
  Call Number CAT @ cat @ ASV2010a Serial 1325  
Permanent link to this record
 

 
Author Naveen Onkarappa; Angel Sappa edit  doi
isbn  openurl
  Title On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow Type Conference Article
  Year 2010 Publication 7th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume (down) 6111 Issue Pages 230-239  
  Keywords  
  Abstract This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.  
  Address Povoa de Varzim (Portugal)  
  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 978-3-642-13771-6 Medium  
  Area Expedition Conference ICIAR  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ OnS2010 Serial 1342  
Permanent link to this record
 

 
Author Salim Jouili; Salvatore Tabbone; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title Comparing Graph Similarity Measures for Graphical Recognition Type Book Chapter
  Year 2010 Publication Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers Abbreviated Journal  
  Volume (down) 6020 Issue Pages 37-48  
  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  
  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 978-3-642-13727-3 Medium  
  Area Expedition Conference GREC  
  Notes DAG Approved no  
  Call Number Admin @ si @ JTV2010 Serial 2404  
Permanent link to this record
 

 
Author Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) edit  isbn
openurl 
  Title Graphics Recognition: Achievements, Challenges, and Evolution Type Book Whole
  Year 2010 Publication 8th International Workshop GREC 2009. Abbreviated Journal  
  Volume (down) 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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