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Author Katerine Diaz; Francesc J. Ferri; W. Diaz edit  doi
isbn  openurl
  Title Fast Approximated Discriminative Common Vectors using rank-one SVD updates Type Conference Article
  Year 2013 Publication 20th International Conference On Neural Information Processing Abbreviated Journal  
  Volume (up) 8228 Issue III Pages 368-375  
  Keywords  
  Abstract An efficient incremental approach to the discriminative common vector (DCV) method for dimensionality reduction and classification is presented. The proposal consists of a rank-one update along with an adaptive restriction on the rank of the null space which leads to an approximate but convenient solution. The algorithm can be implemented very efficiently in terms of matrix operations and space complexity, which enables its use in large-scale dynamic application domains. Deep comparative experimentation using publicly available high dimensional image datasets has been carried out in order to properly assess the proposed algorithm against several recent incremental formulations.
K. Diaz-Chito, F.J. Ferri, W. Diaz
 
  Address Daegu; Korea; November 2013  
  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 978-3-642-42050-4 Medium  
  Area Expedition Conference ICONIP  
  Notes ADAS Approved no  
  Call Number Admin @ si @ DFD2013 Serial 2439  
Permanent link to this record
 

 
Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez edit   pdf
doi  isbn
openurl 
  Title On-line lumen centre detection in gastrointestinal and respiratory endoscopy Type Conference Article
  Year 2013 Publication Second International Workshop Clinical Image-Based Procedures Abbreviated Journal  
  Volume (up) 8361 Issue Pages 31-38  
  Keywords Lumen centre detection; Bronchoscopy; Colonoscopy  
  Abstract We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).  
  Address Nagoya; Japan; September 2013  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-05665-4 Medium  
  Area 800 Expedition Conference CLIP  
  Notes MV; IAM; 600.047; 600.044; 600.060 Approved no  
  Call Number Admin @ si @ SBG2013 Serial 2302  
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Author Juan Ramon Terven Salinas; Joaquin Salas; Bogdan Raducanu edit  doi
isbn  openurl
  Title Robust Head Gestures Recognition for Assistive Technology Type Book Chapter
  Year 2014 Publication Pattern Recognition Abbreviated Journal  
  Volume (up) 8495 Issue Pages 152-161  
  Keywords  
  Abstract This paper presents a system capable of recognizing six head gestures: nodding, shaking, turning right, turning left, looking up, and looking down. The main difference of our system compared to other methods is that the Hidden Markov Models presented in this paper, are fully connected and consider all possible states in any given order, providing the following advantages to the system: (1) allows unconstrained movement of the head and (2) it can be easily integrated into a wearable device (e.g. glasses, neck-hung devices), in which case it can robustly recognize gestures in the presence of ego-motion. Experimental results show that this approach outperforms common methods that use restricted HMMs for each gesture.  
  Address  
  Corporate Author Thesis  
  Publisher Springer International Publishing 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 978-3-319-07490-0 Medium  
  Area Expedition Conference  
  Notes OR;MV Approved no  
  Call Number Admin @ si @ TSR2014b Serial 2505  
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Author Oualid M. Benkarim; Petia Radeva; Laura Igual edit   pdf
doi  isbn
openurl 
  Title Label Consistent Multiclass Discriminative Dictionary Learning for MRI Segmentation Type Conference Article
  Year 2014 Publication 8th Conference on Articulated Motion and Deformable Objects Abbreviated Journal  
  Volume (up) 8563 Issue Pages 138-147  
  Keywords MRI segmentation; sparse representation; discriminative dic- tionary learning; multiclass classi cation  
  Abstract The automatic segmentation of multiple subcortical structures in brain Magnetic Resonance Images (MRI) still remains a challenging task. In this paper, we address this problem using sparse representation and discriminative dictionary learning, which have shown promising results in compression, image denoising and recently in MRI segmentation. Particularly, we use multiclass dictionaries learned from a set of brain atlases to simultaneously segment multiple subcortical structures.
We also impose dictionary atoms to be specialized in one given class using label consistent K-SVD, which can alleviate the bias produced by unbalanced libraries, present when dealing with small structures. The proposed method is compared with other state of the art approaches for the segmentation of the Basal Ganglia of 35 subjects of a public dataset.
The promising results of the segmentation method show the eciency of the multiclass discriminative dictionary learning algorithms in MRI segmentation problems.
 
  Address Palma de Mallorca; July 2014  
  Corporate Author Thesis  
  Publisher Springer International Publishing 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 978-3-319-08848-8 Medium  
  Area Expedition Conference AMDO  
  Notes MILAB; OR Approved no  
  Call Number Admin @ si @ BRI2014 Serial 2494  
Permanent link to this record
 

 
Author Marc Bolaños; Maite Garolera; Petia Radeva edit  doi
openurl 
  Title Video Segmentation of Life-Logging Videos Type Conference Article
  Year 2014 Publication 8th Conference on Articulated Motion and Deformable Objects Abbreviated Journal  
  Volume (up) 8563 Issue Pages 1-9  
  Keywords  
  Abstract  
  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 AMDO  
  Notes MILAB Approved no  
  Call Number Admin @ si @ BGR2014 Serial 2558  
Permanent link to this record
 

 
Author Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo edit   pdf
doi  openurl
  Title Chromatic induction and contrast masking: similar models, different goals? Type Conference Article
  Year 2013 Publication Human Vision and Electronic Imaging XVIII Abbreviated Journal  
  Volume (up) 8651 Issue Pages  
  Keywords  
  Abstract Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.  
  Address San Francisco CA; USA; February 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 HVEI  
  Notes CIC Approved no  
  Call Number Admin @ si @ JOL2013 Serial 2240  
Permanent link to this record
 

 
Author Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title Polyp Segmentation Method in Colonoscopy Videos by means of MSA-DOVA Energy Maps Calculation Type Conference Article
  Year 2014 Publication 3rd MICCAI Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal  
  Volume (up) 8680 Issue Pages 41-49  
  Keywords Image segmentation; Polyps; Colonoscopy; Valley information; Energy maps  
  Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.  
  Address Boston; USA; September 2014  
  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 CLIP  
  Notes MV; 600.060; 600.044; 600.047;SIAI Approved no  
  Call Number Admin @ si @ BNS2014 Serial 2502  
Permanent link to this record
 

 
Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
doi  isbn
openurl 
  Title A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 7-11  
  Keywords Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel  
  Abstract Product graph has been shown as a way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. Here we focus on the two major limitations of the previous version of the algorithm: (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 edge graph representation on the original graph representing the graphical information and the product graph is computed between the dual edge graphs of the pattern graph and the target graph. The dual edge 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 the pair of similar edges of two operand graphs and exponentiating the adjacency matrix finds similar random walks of greater lengths. Nodes joining similar random walks between two graphs are found by combining different weighted exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ DLB2014 Serial 2698  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez edit  doi
isbn  openurl
  Title Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 109-121  
  Keywords Graphics recognition; Floor plan analysis; Object segmentation  
  Abstract In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions.  
  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 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.076; 600.077 Approved no  
  Call Number Admin @ si @ HVS2014 Serial 2535  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados edit  doi
isbn  openurl
  Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 135-146  
  Keywords Graphics recognition; Graphics retrieval; Image classification  
  Abstract This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.  
  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 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 Approved no  
  Call Number Admin @ si @ HFF2014 Serial 2536  
Permanent link to this record
 

 
Author Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta edit  doi
isbn  openurl
  Title The ICDAR/GREC 2013 Music Scores Competition: Staff Removal Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 207-220  
  Keywords Competition; Graphics recognition; Music scores; Writer identification; Staff removal  
  Abstract The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor B.Lamiroy; J.-M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077; 600.061 Approved no  
  Call Number Admin @ si @ FKV2014 Serial 2581  
Permanent link to this record
 

 
Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 25-37  
  Keywords  
  Abstract Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ BDJ2014 Serial 2699  
Permanent link to this record
 

 
Author Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit  doi
isbn  openurl
  Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 3-10  
  Keywords  
  Abstract In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.055; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ RKL2014 Serial 2700  
Permanent link to this record
 

 
Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Classification of Administrative Document Images by Logo Identification Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume (up) 8746 Issue Pages 49-58  
  Keywords Administrative Document Classification; Logo Recognition; Logo Spotting  
  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  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.045; 605.203; 600.077 Approved no  
  Call Number Admin @ si @ RPK2014 Serial 2701  
Permanent link to this record
 

 
Author Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades edit   pdf
doi  isbn
openurl 
  Title Exploring the impact of inter-query variability on the performance of retrieval systems Type Conference Article
  Year 2014 Publication 11th International Conference on Image Analysis and Recognition Abbreviated Journal  
  Volume (up) 8814 Issue Pages 413–420  
  Keywords  
  Abstract This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes.  
  Address Algarve; Portugal; October 2014  
  Corporate Author Thesis  
  Publisher Springer International Publishing 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 978-3-319-11757-7 Medium  
  Area Expedition Conference ICIAR  
  Notes IAM; DAG; 600.060; 600.061; 600.077; 600.075 Approved no  
  Call Number Admin @ si @ BGB2014 Serial 2559  
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