toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester edit   pdf
url  doi
openurl 
  Title (up) Geometric Steerable Medial Maps Type Journal Article
  Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA  
  Volume 24 Issue 6 Pages 1255-1266  
  Keywords Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction  
  Abstract In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume.
 
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Mubarak Shah  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes IAM; 605.203; 600.060; 600.044 Approved no  
  Call Number IAM @ iam @ VGB2013 Serial 2192  
Permanent link to this record
 

 
Author Victor Borjas; Jordi Vitria; Petia Radeva edit   pdf
openurl 
  Title (up) Gradient Histogram Background Modeling for People Detection in Stationary Camera Environments Type Conference Article
  Year 2013 Publication 13th IAPR Conference on Machine Vision Applications Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Best Poster AwardOne of the big challenges of today person detectors is the decreasing of the false positive rate. In this paper, we propose a novel framework to customize person detectors in static camera scenarios in order to reduce this rate. This scheme includes background modeling for subtraction based on gradient histograms and Mean-Shift clustering. Our experiments show that the detection improved compared to using only the output from the pedestrian detector reducing 87% of the false positives and therefore the overall precision of the detection
was increased signi cantly.
 
  Address Kyoto; Japan; May 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 MVA  
  Notes OR; MILAB;MV Approved no  
  Call Number BVR2013 Serial 2238  
Permanent link to this record
 

 
Author Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos edit   pdf
doi  isbn
openurl 
  Title (up) Handwriting Recognition in Historical Documents using Very Large Vocabularies Type Conference Article
  Year 2013 Publication 2nd International Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 67-72  
  Keywords  
  Abstract Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words.  
  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 ISBN 978-1-4503-2115-0 Medium  
  Area Expedition Conference HIP  
  Notes DAG; 600.056; 600.045; 600.061; 602.006; 602.101 Approved no  
  Call Number Admin @ si @ FFM2013 Serial 2296  
Permanent link to this record
 

 
Author Francisco Cruz; Oriol Ramos Terrades edit   pdf
doi  openurl
  Title (up) Handwritten Line Detection via an EM Algorithm Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 718-722  
  Keywords  
  Abstract In this paper we present a handwritten line segmentation method devised to work on documents composed of several paragraphs with multiple line orientations. The method is based on a variation of the EM algorithm for the estimation of a set of regression lines between the connected components that compose the image. We evaluated our method on the ICDAR2009 handwriting segmentation contest dataset with promising results that overcome most of the presented methods. In addition, we prove the usability of the presented method by performing line segmentation on the George Washington database obtaining encouraging results.  
  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 Approved no  
  Call Number Admin @ si @ CrT2013 Serial 2329  
Permanent link to this record
 

 
Author Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny edit   pdf
doi  openurl
  Title (up) Handwritten Word Spotting with Corrected Attributes Type Conference Article
  Year 2013 Publication 15th IEEE International Conference on Computer Vision Abbreviated Journal  
  Volume Issue Pages 1017-1024  
  Keywords  
  Abstract We propose an approach to multi-writer word spotting, where the goal is to find a query word in a dataset comprised of document images. We propose an attributes-based approach that leads to a low-dimensional, fixed-length representation of the word images that is fast to compute and, especially, fast to compare. This approach naturally leads to an unified representation of word images and strings, which seamlessly allows one to indistinctly perform query-by-example, where the query is an image, and query-by-string, where the query is a string. We also propose a calibration scheme to correct the attributes scores based on Canonical Correlation Analysis that greatly improves the results on a challenging dataset. We test our approach on two public datasets showing state-of-the-art results.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN Medium  
  Area Expedition Conference ICCV  
  Notes DAG Approved no  
  Call Number Admin @ si @ AGF2013 Serial 2327  
Permanent link to this record
 

 
Author Ferran Poveda; Debora Gil; Enric Marti; Albert Andaluz; Manel Ballester;Francesc Carreras Costa edit   pdf
url  doi
openurl 
  Title (up) Helical structure of the cardiac ventricular anatomy assessed by Diffusion Tensor Magnetic Resonance Imaging multi-resolution tractography Type Journal Article
  Year 2013 Publication Revista Española de Cardiología Abbreviated Journal REC  
  Volume 66 Issue 10 Pages 782-790  
  Keywords Heart;Diffusion magnetic resonance imaging;Diffusion tractography;Helical heart;Myocardial ventricular band.  
  Abstract Deep understanding of myocardial structure linking morphology and function of the heart would unravel crucial knowledge for medical and surgical clinical procedures and studies. Several conceptual models of myocardial fiber organization have been proposed but the lack of an automatic and objective methodology prevented an agreement. We sought to deepen in this knowledge through advanced computer graphic representations of the myocardial fiber architecture by diffusion tensor magnetic resonance imaging (DT-MRI).
We performed automatic tractography reconstruction of unsegmented DT-MRI canine heart datasets coming from the public database of the Johns Hopkins University. Full scale tractographies have been build with 200 seeds and are composed by streamlines computed on the vectorial field of primary eigenvectors given at the diffusion tensor volumes. Also, we introduced a novel multi-scale visualization technique in order to obtain a simplified tractography. This methodology allowed to keep the main geometric features of the fiber tracts, making easier to decipher the main properties of the architectural organization of the heart.
On the analysis of the output from our tractographic representations we found exact correlation with low-level details of myocardial architecture, but also with the more abstract conceptualization of a continuous helical ventricular myocardial fiber array.
Objective analysis of myocardial architecture by an automated method, including the entire myocardium and using several 3D levels of complexity, reveals a continuous helical myocardial fiber arrangement of both right and left ventricles, supporting the anatomical model of the helical ventricular myocardial band described by Torrent-Guasp.
 
  Address  
  Corporate Author Thesis  
  Publisher Elsevier 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  
  Notes IAM; 600.044; 600.060 Approved no  
  Call Number IAM @ iam @ PGM2013 Serial 2194  
Permanent link to this record
 

 
Author Francisco Javier Orozco; Ognjen Rudovic; Jordi Gonzalez; Maja Pantic edit   pdf
url  doi
openurl 
  Title (up) Hierarchical On-line Appearance-Based Tracking for 3D Head Pose, Eyebrows, Lips, Eyelids and Irises Type Journal Article
  Year 2013 Publication Image and Vision Computing Abbreviated Journal IMAVIS  
  Volume 31 Issue 4 Pages 322-340  
  Keywords On-line appearance models; Levenberg–Marquardt algorithm; Line-search optimization; 3D face tracking; Facial action tracking; Eyelid tracking; Iris tracking  
  Abstract In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time.  
  Address  
  Corporate Author Thesis  
  Publisher Elsevier 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  
  Notes ISE; 605.203; 302.012; 302.018; 600.049 Approved no  
  Call Number ORG2013 Serial 2221  
Permanent link to this record
 

 
Author Bhaskar Chakraborty; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca edit   pdf
doi  openurl
  Title (up) Human Action Recognition Using an Ensemble of Body-Part Detectors Type Journal Article
  Year 2013 Publication Expert Systems Abbreviated Journal EXSY  
  Volume 30 Issue 2 Pages 101-114  
  Keywords Human action recognition;body-part detection;hidden Markov model  
  Abstract This paper describes an approach to human action recognition based on a probabilistic optimization model of body parts using hidden Markov model (HMM). Our method is able to distinguish between similar actions by only considering the body parts having major contribution to the actions, for example, legs for walking, jogging and running; arms for boxing, waving and clapping. We apply HMMs to model the stochastic movement of the body parts for action recognition. The HMM construction uses an ensemble of body-part detectors, followed by grouping of part detections, to perform human identification. Three example-based body-part detectors are trained to detect three components of the human body: the head, legs and arms. These detectors cope with viewpoint changes and self-occlusions through the use of ten sub-classifiers that detect body parts over a specific range of viewpoints. Each sub-classifier is a support vector machine trained on features selected for the discriminative power for each particular part/viewpoint combination. Grouping of these detections is performed using a simple geometric constraint model that yields a viewpoint-invariant human detector. We test our approach on three publicly available action datasets: the KTH dataset, Weizmann dataset and HumanEva dataset. Our results illustrate that with a simple and compact representation we can achieve robust recognition of human actions comparable to the most complex, state-of-the-art methods.  
  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  
  Notes ISE Approved no  
  Call Number Admin @ si @ CBG2013 Serial 1809  
Permanent link to this record
 

 
Author Daniel Sanchez; J.C.Ortega; Miguel Angel Bautista edit   pdf
doi  isbn
openurl 
  Title (up) Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization Type Conference Article
  Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 7887 Issue Pages 50-58  
  Keywords Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts  
  Abstract Human body segmentation is a hard task because of the high variability in appearance produced by changes in the point of view, lighting conditions, and number of articulations of the human body. In this paper, we propose a two-stage approach for the segmentation of the human body. In a first step, a set of human limbs are described, normalized to be rotation invariant, and trained using cascade of classifiers to be split in a tree structure way. Once the tree structure is trained, it is included in a ternary Error-Correcting Output Codes (ECOC) framework. This first classification step is applied in a windowing way on a new test image, defining a body-like probability map, which is used as an initialization of a GMM color modelling and binary Graph Cuts optimization procedure. The proposed methodology is tested in a novel limb-labelled data set. Results show performance improvements of the novel approach in comparison to classical cascade of classifiers and human detector-based Graph Cuts segmentation approaches.  
  Address Madeira; Portugal; June 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 978-3-642-38627-5 Medium  
  Area Expedition Conference IbPRIA  
  Notes HUPBA Approved no  
  Call Number SOB2013 Serial 2250  
Permanent link to this record
 

 
Author Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados edit   pdf
doi  isbn
openurl 
  Title (up) Hybrid grammar language model for handwritten historical documents recognition Type Conference Article
  Year 2013 Publication 6th Iberian Conference on Pattern Recognition and Image Analysis Abbreviated Journal  
  Volume 7887 Issue Pages 117-124  
  Keywords  
  Abstract In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate.  
  Address Madeira; Portugal; June 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 978-3-642-38627-5 Medium  
  Area Expedition Conference IbPRIA  
  Notes DAG; 602.006; 600.045; 600.061 Approved no  
  Call Number Admin @ si @ CFF2013 Serial 2292  
Permanent link to this record
 

 
Author Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras edit   pdf
doi  openurl
  Title (up) ICDAR 2013 Robust Reading Competition Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1484-1493  
  Keywords  
  Abstract This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods.  
  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; 600.056 Approved no  
  Call Number Admin @ si @ KSU2013 Serial 2318  
Permanent link to this record
 

 
Author Shida Beigpour edit  openurl
  Title (up) Illumination and object reflectance modeling Type Book Whole
  Year 2013 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract More realistic and accurate models of the scene illumination and object reflectance can greatly improve the quality of many computer vision and computer graphics tasks. Using such model, a more profound knowledge about the interaction of light with object surfaces can be established which proves crucial to a variety of computer vision applications. In the current work, we investigate the various existing approaches to illumination and reflectance modeling and form an analysis on their shortcomings in capturing the complexity of real-world scenes. Based on this analysis we propose improvements to different aspects of reflectance and illumination estimation in order to more realistically model the real-world scenes in the presence of complex lighting phenomena (i.e, multiple illuminants, interreflections and shadows). Moreover, we captured our own multi-illuminant dataset which consists of complex scenes and illumination conditions both outdoor and in laboratory conditions. In addition we investigate the use of synthetic data to facilitate the construction of datasets and improve the process of obtaining ground-truth information.  
  Address Barcelona  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Joost Van de Weijer;Ernest Valveny  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC Approved no  
  Call Number Admin @ si @ Bei2013 Serial 2267  
Permanent link to this record
 

 
Author Jorge Bernal; F. Javier Sanchez; Fernando Vilariño edit   pdf
doi  openurl
  Title (up) Impact of Image Preprocessing Methods on Polyp Localization in Colonoscopy Frames Type Conference Article
  Year 2013 Publication 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Abbreviated Journal  
  Volume Issue Pages 7350 - 7354  
  Keywords  
  Abstract In this paper we present our image preprocessing methods as a key part of our automatic polyp localization scheme. These methods are used to assess the impact of different endoluminal scene elements when characterizing polyps. More precisely we tackle the influence of specular highlights, blood vessels and black mask surrounding the scene. Experimental results prove that the appropriate handling of these elements leads to a great improvement in polyp localization results.  
  Address Osaka; Japan; July 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 1557-170X ISBN Medium  
  Area 800 Expedition Conference EMBC  
  Notes MV; 600.047; 600.060;SIAI Approved no  
  Call Number Admin @ si @ BSV2013 Serial 2286  
Permanent link to this record
 

 
Author Andreas Fischer; Volkmar Frinken; Horst Bunke; Ching Y. Suen edit   pdf
doi  openurl
  Title (up) Improving HMM-Based Keyword Spotting with Character Language Models Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 506-510  
  Keywords  
  Abstract Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a high performance when compared with traditional template image matching. In the lexicon-free approach pursued, only the text appearance was taken into account for recognition. In this paper, we integrate character n-gram language models into the spotting system in order to provide an additional language context. On the modern IAM database as well as the historical George Washington database, we demonstrate that character language models significantly improve the spotting performance.  
  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; 605.203 Approved no  
  Call Number Admin @ si @ FFB2013 Serial 2295  
Permanent link to this record
 

 
Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados edit   pdf
doi  openurl
  Title (up) Integrating Visual and Textual Cues for Query-by-String Word Spotting Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 511 - 515  
  Keywords  
  Abstract In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.  
  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; ADAS; 600.045; 600.055; 600.061 Approved no  
  Call Number Admin @ si @ ART2013 Serial 2224  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: