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| Author | Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier | ||||
| Title | Normalisation et validation d'images de documents capturées en mobilité | Type | Conference Article | ||
| Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
| Volume | Issue | Pages | 109-124 | ||
| Keywords | mobile document image acquisition; perspective correction; illumination correction; quality assessment; focus measure; OCR accuracy prediction | ||||
Abstract  |
Mobile document image acquisition integrates many distortions which must be corrected or detected on the device, before the document becomes unavailable or paying data transmission fees. In this paper, we propose a system to correct perspective and illumination issues, and estimate the sharpness of the image for OCR recognition. The correction step relies on fast and accurate border detection followed by illumination normalization. Its evaluation on a private dataset shows a clear improvement on OCR accuracy. The quality assessment
step relies on a combination of focus measures. Its evaluation on a public dataset shows that this simple method compares well to state of the art, learning-based methods which cannot be embedded on a mobile, and outperforms metric-based methods. |
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| Address | Nancy; France; March 2014 | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CIFED | ||
| Notes | DAG; 601.223; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RCO2014b | Serial | 2546 | ||
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| Author | Pedro Martins; Paulo Carvalho; Carlo Gatta | ||||
| Title | Context-aware features and robust image representations | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Visual Communication and Image Representation | Abbreviated Journal | JVCIR |
| Volume | 25 | Issue | 2 | Pages | 339-348 |
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| Abstract |
Local image features are often used to efficiently represent image content. The limited number of types of features that a local feature extractor responds to might be insufficient to provide a robust image representation. To overcome this limitation, we propose a context-aware feature extraction formulated under an information theoretic framework. The algorithm does not respond to a specific type of features; the idea is to retrieve complementary features which are relevant within the image context. We empirically validate the method by investigating the repeatability, the completeness, and the complementarity of context-aware features on standard benchmarks. In a comparison with strictly local features, we show that our context-aware features produce more robust image representations. Furthermore, we study the complementarity between strictly local features and context-aware ones to produce an even more robust representation. | ||||
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| Area | Expedition | Conference | |||
| Notes | LAMP; 600.079;MILAB | Approved | no | ||
| Call Number | Admin @ si @ MCG2014 | Serial | 2467 | ||
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| Author | Clement Guerin; Christophe Rigaud; Karell Bertet; Jean-Christophe Burie; Arnaud Revel ; Jean-Marc Ogier | ||||
| Title | Réduction de l’espace de recherche pour les personnages de bandes dessinées | Type | Conference Article | ||
| Year | 2014 | Publication | 19th National Congress Reconnaissance de Formes et l'Intelligence Artificielle | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | contextual search; document analysis; comics characters | ||||
| Abstract |
Les bandes dessinées représentent un patrimoine culturel important dans de nombreux pays et leur numérisation massive offre la possibilité d'effectuer des recherches dans le contenu des images. À ce jour, ce sont principalement les structures des pages et leurs contenus textuels qui ont été étudiés, peu de travaux portent sur le contenu graphique. Nous proposons de nous appuyer sur des éléments déjà étudiés tels que la position des cases et des bulles, pour réduire l'espace de recherche et localiser les personnages en fonction de la queue des bulles. L'évaluation de nos différentes contributions à partir de la base eBDtheque montre un taux de détection des queues de bulle de 81.2%, de localisation des personnages allant jusqu'à 85% et un gain d'espace de recherche de plus de 50%. | ||||
| Address | Rouen; Francia; July 2014 | ||||
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| Area | Expedition | Conference | RFIA | ||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ GRB2014 | Serial | 2480 | ||
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| Author | Christophe Rigaud; Clement Guerin | ||||
| Title | Localisation contextuelle des personnages de bandes dessinées | Type | Conference Article | ||
| Year | 2014 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract |
Les auteurs proposent une méthode de localisation des personnages dans des cases de bandes dessinées en s'appuyant sur les caractéristiques des bulles de dialogue. L'évaluation montre un taux de localisation des personnages allant jusqu'à 65%. | ||||
| Address | Nancy; Francia; March 2014 | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RiG2014 | Serial | 2481 | ||
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| Author | Ricard Balague | ||||
| Title | Exploring the combination of color cues for intrinsic image decomposition | Type | Report | ||
| Year | 2014 | Publication | CVC Technical Report | Abbreviated Journal | |
| Volume | 178 | Issue | Pages | ||
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| Abstract |
Intrinsic image decomposition is a challenging problem that consists in separating an image into its physical characteristics: reflectance and shading. This problem can be solved in different ways, but most methods have combined information from several visual cues. In this work we describe an extension of an existing method proposed by Serra et al. which considers two color descriptors and combines them by means of a Markov Random Field. We analyze in depth the weak points of the method and we explore more possibilities to use in both descriptors. The proposed extension depends on the combination of the cues considered to overcome some of the limitations of the original method. Our approach is tested on the MIT dataset and Beigpour et al. dataset, which contain images of real objects acquired under controlled conditions and synthetic images respectively, with their corresponding ground truth. | ||||
| Address | UAB; September 2014 | ||||
| Corporate Author | Thesis | Master's thesis | |||
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| Notes | CIC; 600.074 | Approved | no | ||
| Call Number | Admin @ si @ Bal2014 | Serial | 2579 | ||
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| Author | Marc Serra; Olivier Penacchio; Robert Benavente; Maria Vanrell; Dimitris Samaras | ||||
| Title | The Photometry of Intrinsic Images | Type | Conference Article | ||
| Year | 2014 | Publication | 27th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1494-1501 | ||
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| Abstract |
Intrinsic characterization of scenes is often the best way to overcome the illumination variability artifacts that complicate most computer vision problems, from 3D reconstruction to object or material recognition. This paper examines the deficiency of existing intrinsic image models to accurately account for the effects of illuminant color and sensor characteristics in the estimation of intrinsic images and presents a generic framework which incorporates insights from color constancy research to the intrinsic image decomposition problem. The proposed mathematical formulation includes information about the color of the illuminant and the effects of the camera sensors, both of which modify the observed color of the reflectance of the objects in the scene during the acquisition process. By modeling these effects, we get a “truly intrinsic” reflectance image, which we call absolute reflectance, which is invariant to changes of illuminant or camera sensors. This model allows us to represent a wide range of intrinsic image decompositions depending on the specific assumptions on the geometric properties of the scene configuration and the spectral properties of the light source and the acquisition system, thus unifying previous models in a single general framework. We demonstrate that even partial information about sensors improves significantly the estimated reflectance images, thus making our method applicable for a wide range of sensors. We validate our general intrinsic image framework experimentally with both synthetic data and natural images. | ||||
| Address | Columbus; Ohio; USA; June 2014 | ||||
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| Area | Expedition | Conference | CVPR | ||
| Notes | CIC; 600.052; 600.051; 600.074 | Approved | no | ||
| Call Number | Admin @ si @ SPB2014 | Serial | 2506 | ||
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| Author | Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
| Title | Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume | 18 | Issue | 6 | Pages | 1831-1838 |
| Keywords | Wireless Capsule Endoscopy; Small Bowel Motility Dysfunction; Contraction Detection; Structured Prediction; Betweenness Centrality | ||||
| Abstract |
Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state of the art performance for this task. | ||||
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| Notes | OR; MILAB; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ SDZ2014 | Serial | 2385 | ||
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| Author | Pierluigi Casale; Oriol Pujol; Petia Radeva | ||||
| Title | Approximate polytope ensemble for one-class classification | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 2 | Pages | 854-864 |
| Keywords | One-class classification; Convex hull; High-dimensionality; Random projections; Ensemble learning | ||||
| Abstract |
In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets. | ||||
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| Notes | MILAB; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ CPR2014a | Serial | 2469 | ||
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| Author | Frederic Sampedro; Sergio Escalera; Anna Puig | ||||
| Title | Iterative Multiclass Multiscale Stacked Sequential Learning: definition and application to medical volume segmentation | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 46 | Issue | Pages | 1-10 | |
| Keywords | Machine learning; Sequential learning; Multi-class problems; Contextual learning; Medical volume segmentation | ||||
| Abstract |
In this work we present the iterative multi-class multi-scale stacked sequential learning framework (IMMSSL), a novel learning scheme that is particularly suited for medical volume segmentation applications. This model exploits the inherent voxel contextual information of the structures of interest in order to improve its segmentation performance results. Without any feature set or learning algorithm prior assumption, the proposed scheme directly seeks to learn the contextual properties of a region from the predicted classifications of previous classifiers within an iterative scheme. Performance results regarding segmentation accuracy in three two-class and multi-class medical volume datasets show a significant improvement with respect to state of the art alternatives. Due to its easiness of implementation and its independence of feature space and learning algorithm, the presented machine learning framework could be taken into consideration as a first choice in complex volume segmentation scenarios. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SEP2014 | Serial | 2550 | ||
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| Author | David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes | ||||
| Title | Sequential Word Spotting in Historical Handwritten Documents | Type | Conference Article | ||
| Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 101 - 105 | ||
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| Abstract |
In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered index pages of family names. |
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| Address | Tours; Francia; April 2014 | ||||
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| ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 600.061; 600.056; 602.006; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ FML2014 | Serial | 2462 | ||
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| Author | Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio | ||||
| Title | A computational framework for cancer response assessment based on oncological PET-CT scans | Type | Journal Article | ||
| Year | 2014 | Publication | Computers in Biology and Medicine | Abbreviated Journal | CBM |
| Volume | 55 | Issue | Pages | 92–99 | |
| Keywords | Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis | ||||
| Abstract |
In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SED2014 | Serial | 2606 | ||
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| Author | Agata Lapedriza; David Masip; David Sanchez | ||||
| Title | Emotions Classification using Facial Action Units Recognition | Type | Conference Article | ||
| Year | 2014 | Publication | 17th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 269 | Issue | Pages | 55-64 | |
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| Abstract |
In this work we build a system for automatic emotion classification from image sequences. We analyze subtle changes in facial expressions by detecting a subset of 12 representative facial action units (AUs). Then, we classify emotions based on the output of these AUs classifiers, i.e. the presence/absence of AUs. We base the AUs classification upon a set of spatio-temporal geometric and appearance features for facial representation, fusing them within the emotion classifier. A decision tree is trained for emotion classifying, making the resulting model easy to interpret by capturing the combination of AUs activation that lead to a particular emotion. For Cohn-Kanade database, the proposed system classifies 7 emotions with a mean accuracy of near 90%, attaining a similar recognition accuracy in comparison with non-interpretable models that are not based in AUs detection. | ||||
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| ISSN | ISBN | 978-1-61499-451-0 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ LMS2014 | Serial | 2622 | ||
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| Author | Frederic Sampedro; Anna Domenech; Sergio Escalera | ||||
| Title | Static and dynamic computational cancer spread quantification in whole body FDG-PET/CT scans | Type | Journal Article | ||
| Year | 2014 | Publication | Journal of Medical Imaging and Health Informatics | Abbreviated Journal | JMIHI |
| Volume | 4 | Issue | 6 | Pages | 825-831 |
| Keywords | CANCER SPREAD; COMPUTER AIDED DIAGNOSIS; MEDICAL IMAGING; TUMOR QUANTIFICATION | ||||
| Abstract |
In this work we address the computational cancer spread quantification scenario in whole body FDG-PET/CT scans. At the static level, this setting can be modeled as a clustering problem on the set of 3D connected components of the whole body PET tumoral segmentation mask carried out by nuclear medicine physicians. At the dynamic level, and ad-hoc algorithm is proposed in order to quantify the cancer spread time evolution which, when combined with other existing indicators, gives rise to the metabolic tumor volume-aggressiveness-spread time evolution chart, a novel tool that we claim that would prove useful in nuclear medicine and oncological clinical or research scenarios. Good performance results of the proposed methodologies both at the clinical and technological level are shown using a dataset of 48 segmented whole body FDG-PET/CT scans. | ||||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | Admin @ si @ SDE2014b | Serial | 2548 | ||
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| Author | Marçal Rusiñol; Josep Llados | ||||
| Title | Boosting the Handwritten Word Spotting Experience by Including the User in the Loop | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 3 | Pages | 1063–1072 |
| Keywords | Handwritten word spotting; Query by example; Relevance feedback; Query fusion; Multidimensional scaling | ||||
| Abstract |
In this paper, we study the effect of taking the user into account in a query-by-example handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and two baseline word spotting approaches both based on the bag-of-visual-words model. We finally present two alternative ways of presenting the results to the user that might be more attractive and suitable to the user's needs than the classic ranked list. | ||||
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| ISSN | 0031-3203 | ISBN | Medium | ||
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| Notes | DAG; 600.045; 600.061; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RuL2013 | Serial | 2343 | ||
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| Author | Carlo Gatta; Adriana Romero; Joost Van de Weijer | ||||
| Title | Unrolling loopy top-down semantic feedback in convolutional deep networks | Type | Conference Article | ||
| Year | 2014 | Publication | Workshop on Deep Vision: Deep Learning for Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 498-505 | ||
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| Abstract |
In this paper, we propose a novel way to perform top-down semantic feedback in convolutional deep networks for efficient and accurate image parsing. We also show how to add global appearance/semantic features, which have shown to improve image parsing performance in state-of-the-art methods, and was not present in previous convolutional approaches. The proposed method is characterised by an efficient training and a sufficiently fast testing. We use the well known SIFTflow dataset to numerically show the advantages provided by our contributions, and to compare with state-of-the-art image parsing convolutional based approaches. | ||||
| Address | Columbus; Ohio; June 2014 | ||||
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| Area | Expedition | Conference | CVPRW | ||
| Notes | LAMP; MILAB; 601.160; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ GRW2014 | Serial | 2490 | ||
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