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| Author | Monica Piñol | ||||
| Title | Reinforcement Learning of Visual Descriptors for Object Recognition | Type | Book Whole | ||
Year  |
2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The human visual system is able to recognize the object in an image even if the object is partially occluded, from various points of view, in different colors, or with independence of the distance to the object. To do this, the eye obtains an image and extracts features that are sent to the brain, and then, in the brain the object is recognized. In computer vision, the object recognition branch tries to learns from the human visual system behaviour to achieve its goal. Hence, an algorithm is used to identify representative features of the scene (detection), then another algorithm is used to describe these points (descriptor) and finally the extracted information is used for classifying the object in the scene. The selection of this set of algorithms is a very complicated task and thus, a very active research field. In this thesis we are focused on the selection/learning of the best descriptor for a given image. In the state of the art there are several descriptors but we do not know how to choose the best descriptor because depends on scenes that we will use (dataset) and the algorithm chosen to do the classification. We propose a framework based on reinforcement learning and bag of features to choose the best descriptor according to the given image. The system can analyse the behaviour of different learning algorithms and descriptor sets. Furthermore the proposed framework for improving the classification/recognition ratio can be used with minor changes in other computer vision fields, such as video retrieval. | ||||
| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Ricardo Toledo;Angel Sappa | |
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-5-7 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ Piñ2014 | Serial | 2464 | ||
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| Author | Anjan Dutta | ||||
| Title | Inexact Subgraph Matching Applied to Symbol Spotting in Graphical Documents | Type | Book Whole | ||
| Year |
2014 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | There is a resurgence in the use of structural approaches in the usual object recognition and retrieval problem. Graph theory, in particular, graph matching plays a relevant role in that. Specifically, the detection of an object (or a part of that) in an image in terms of structural features can be formulated as a subgraph matching. Subgraph matching is a challenging task. Specially due to the presence of outliers most of the graph matching algorithms do not perform well in subgraph matching scenario. Also exact subgraph isomorphism has proven to be an NP-complete problem. So naturally, in graph matching community, there are lot of efforts addressing the problem of subgraph matching within suboptimal bound. Most of them work with approximate algorithms that try to get an inexact solution in estimated way. In addition, usual recognition must cope with distortion. Inexact graph matching consists in finding the best isomorphism under a similarity measure. Theoretically this thesis proposes algorithms for solving subgraph matching in an approximate and inexact way.
We consider the symbol spotting problem on graphical documents or line drawings from application point of view. This is a well known problem in the graphics recognition community. It can be further applied for indexing and classification of documents based on their contents. The structural nature of this kind of documents easily motivates one for giving a graph based representation. So the symbol spotting problem on graphical documents can be considered as a subgraph matching problem. The main challenges in this application domain is the noise and distortions that might come during the usage, digitalization and raster to vector conversion of those documents. Apart from that computer vision nowadays is not any more confined within a limited number of images. So dealing a huge number of images with graph based method is a further challenge. In this thesis, on one hand, we have worked on efficient and robust graph representation to cope with the noise and distortions coming from documents. On the other hand, we have worked on different graph based methods and framework to solve the subgraph matching problem in a better approximated way, which can also deal with considerable number of images. Firstly, we propose a symbol spotting method by hashing serialized subgraphs. Graph serialization allows to create factorized substructures such as graph paths, which can be organized in hash tables depending on the structural similarities of the serialized subgraphs. The involvement of hashing techniques helps to reduce the search space substantially and speeds up the spotting procedure. Secondly, we introduce contextual similarities based on the walk based propagation on tensor product graph. These contextual similarities involve higher order information and more reliable than pairwise similarities. We use these higher order similarities to formulate subgraph matching as a node and edge selection problem in the tensor product graph. Thirdly, we propose near convex grouping to form near convex region adjacency graph which eliminates the limitations of traditional region adjacency graph representation for graphic recognition. Fourthly, we propose a hierarchical graph representation by simplifying/correcting the structural errors to create a hierarchical graph of the base graph. Later these hierarchical graph structures are matched with some graph matching methods. Apart from that, in this thesis we have provided an overall experimental comparison of all the methods and some of the state-of-the-art methods. Furthermore, some dataset models have also been proposed. |
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| Address | |||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Josep Llados;Umapada Pal | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940902-4-0 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ Dut2014 | Serial | 2465 | ||
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| Author | Carlo Gatta; Francesco Ciompi | ||||
| Title | Stacked Sequential Scale-Space Taylor Context | Type | Journal Article | ||
| Year |
2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 36 | Issue | 8 | Pages | 1694-1700 |
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| Abstract | We analyze sequential image labeling methods that sample the posterior label field in order to gather contextual information. We propose an effective method that extracts local Taylor coefficients from the posterior at different scales. Results show that our proposal outperforms state-of-the-art methods on MSRC-21, CAMVID, eTRIMS8 and KAIST2 data sets. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0162-8828 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | LAMP; MILAB; 601.160; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ GaC2014 | Serial | 2466 | ||
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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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| Notes | LAMP; 600.079;MILAB | Approved | no | ||
| Call Number | Admin @ si @ MCG2014 | Serial | 2467 | ||
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| Author | Simeon Petkov; Xavier Carrillo; Petia Radeva; Carlo Gatta | ||||
| Title | Diaphragm border detection in coronary X-ray angiographies: New method and applications | Type | Journal Article | ||
| Year |
2014 | Publication | Computerized Medical Imaging and Graphics | Abbreviated Journal | CMIG |
| Volume | 38 | Issue | 4 | Pages | 296-305 |
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| Abstract | X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation. | ||||
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| Notes | MILAB; LAMP; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ PCR2014 | Serial | 2468 | ||
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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 | Francesco Ciompi; Oriol Pujol; Petia Radeva | ||||
| Title | ECOC-DRF: Discriminative random fields based on error correcting output codes | Type | Journal Article | ||
| Year |
2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 6 | Pages | 2193-2204 |
| Keywords | Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models | ||||
| Abstract | We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments. | ||||
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| Notes | LAMP; HuPBA; MILAB; 605.203; 600.046; 601.043; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ CPR2014b | Serial | 2470 | ||
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| Author | Adriana Romero; Petia Radeva; Carlo Gatta | ||||
| Title | No more meta-parameter tuning in unsupervised sparse feature learning | Type | Miscellaneous | ||
| Year |
2014 | Publication | Arxiv | Abbreviated Journal | |
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| Abstract | CoRR abs/1402.5766
We propose a meta-parameter free, off-the-shelf, simple and fast unsupervised feature learning algorithm, which exploits a new way of optimizing for sparsity. Experiments on STL-10 show that the method presents state-of-the-art performance and provides discriminative features that generalize well. |
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| Notes | MILAB; LAMP; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ RRG2014 | Serial | 2471 | ||
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| Author | P. Ricaurte ; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
| Title | Feature Point Descriptors: Infrared and Visible Spectra | Type | Journal Article | ||
| Year |
2014 | Publication | Sensors | Abbreviated Journal | SENS |
| Volume | 14 | Issue | 2 | Pages | 3690-3701 |
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| Abstract | This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. | ||||
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| Notes | ADAS;600.055; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ RCA2014a | Serial | 2474 | ||
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| Author | Jorge Bernal; Joan M. Nuñez; F. Javier Sanchez; Fernando Vilariño | ||||
| 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 | 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 | ||||
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| Area | Expedition | Conference | CLIP | ||
| Notes | MV; 600.060; 600.044; 600.047;SIAI | Approved | no | ||
| Call Number | Admin @ si @ BNS2014 | Serial | 2502 | ||
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| Author | P. Ricaurte; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
| Title | Performance Evaluation of Feature Point Descriptors in the Infrared Domain | Type | Conference Article | ||
| Year |
2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 1 | Issue | Pages | 545-550 | |
| Keywords | Infrared Imaging; Feature Point Descriptors | ||||
| Abstract | This paper presents a comparative evaluation of classical feature point descriptors when they are used in the long-wave infrared spectral band. Robustness to changes in rotation, scaling, blur, and additive noise are evaluated using a state of the art framework. Statistical results using an outdoor image data set are presented together with a discussion about the differences with respect to the results obtained when images from the visible spectrum are considered. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | ADAS; 600.055; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ RCA2014b | Serial | 2476 | ||
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| Author | Naveen Onkarappa; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa | ||||
| Title | Cross-spectral Stereo Correspondence using Dense Flow Fields | Type | Conference Article | ||
| Year |
2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages | 613-617 | |
| Keywords | Cross-spectral Stereo Correspondence; Dense Optical Flow; Infrared and Visible Spectrum | ||||
| Abstract | This manuscript addresses the cross-spectral stereo correspondence problem. It proposes the usage of a dense flow field based representation instead of the original cross-spectral images, which have a low correlation. In this way, working in the flow field space, classical cost functions can be used as similarity measures. Preliminary experimental results on urban environments have been obtained showing the validity of the proposed approach. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | ADAS; 600.055; 600.076 | Approved | no | ||
| Call Number | Admin @ si @ OAV2014 | Serial | 2477 | ||
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| Author | Ariel Amato; Felipe Lumbreras; Angel Sappa | ||||
| Title | A General-purpose Crowdsourcing Platform for Mobile Devices | Type | Conference Article | ||
| Year |
2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages | 211-215 | |
| Keywords | Crowdsourcing Platform; Mobile Crowdsourcing | ||||
| Abstract | This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | ISE; ADAS; 600.054; 600.055; 600.076; 600.078 | Approved | no | ||
| Call Number | Admin @ si @ ALS2014 | Serial | 2478 | ||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier | ||||
| Title | Color descriptor for content-based drawing retrieval | Type | Conference Article | ||
| Year |
2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 267 - 271 | ||
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| Abstract | Human detection in computer vision field is an active field of research. Extending this to human-like drawings such as the main characters in comic book stories is not trivial. Comics analysis is a very recent field of research at the intersection of graphics, texts, objects and people recognition. The detection of the main comic characters is an essential step towards a fully automatic comic book understanding. This paper presents a color-based approach for comics character retrieval using content-based drawing retrieval and color palette. | ||||
| Address | Tours; Francia; April 2014 | ||||
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| ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 600.056; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RKB2014 | Serial | 2479 | ||
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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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