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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Recoding Error-Correcting Output Codes |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
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Volume |
5519 |
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Pages |
11–21 |
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Abstract |
One of the most widely applied techniques to deal with multi- class categorization problems is the pairwise voting procedure. Recently, this classical approach has been embedded in the Error-Correcting Output Codes framework (ECOC). This framework is based on a coding step, where a set of binary problems are learnt and coded in a matrix, and a decoding step, where a new sample is tested and classified according to a comparison with the positions of the coded matrix. In this paper, we present a novel approach to redefine without retraining, in a problem-dependent way, the one-versus-one coding matrix so that the new coded information increases the generalization capability of the system. Moreover, the final classification can be tuned with the inclusion of a weighting matrix in the decoding step. The approach has been validated over several UCI Machine Learning repository data sets and two real multi-class problems: traffic sign and face categorization. The results show that performance improvements are obtained when comparing the new approach to one of the best ECOC designs (one-versus-one). Furthermore, the novel methodology obtains at least the same performance than the one-versus-one ECOC design. |
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Reykjavik (Iceland) |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02325-5 |
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MCS |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2009d |
Serial |
1190 |
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Author |
Olivier Penacchio |
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Title |
Relative Density of L, M, S photoreceptors in the Human Retina |
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Report |
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Year |
2009 |
Publication |
CVC Technical Report |
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Volume |
135 |
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Computer Vision Center |
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Master's thesis |
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Bellaterra, Barcelona |
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CIC |
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no |
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Admin @ si @ Pen2009 |
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2394 |
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Author |
Murad Al Haj; Andrew Bagdanov; Jordi Gonzalez; Xavier Roca |
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Title |
Robust and Efficient Multipose Face Detection Using Skin Color Segmentation |
Type |
Conference Article |
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Year |
2009 |
Publication |
4th Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
5524 |
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In this paper we describe an efficient technique for detecting faces in arbitrary images and video sequences. The approach is based on segmentation of images or video frames into skin-colored blobs using a pixel-based heuristic. Scale and translation invariant features are then computed from these segmented blobs which are used to perform statistical discrimination between face and non-face classes. We train and evaluate our method on a standard, publicly available database of face images and analyze its performance over a range of statistical pattern classifiers. The generalization of our approach is illustrated by testing on an independent sequence of frames containing many faces and non-faces. These experiments indicate that our proposed approach obtains false positive rates comparable to more complex, state-of-the-art techniques, and that it generalizes better to new data. Furthermore, the use of skin blobs and invariant features requires fewer training samples since significantly fewer non-face candidate regions must be considered when compared to AdaBoost-based approaches. |
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Springer Berlin Heidelberg |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-02171-8 |
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IbPRIA |
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ISE |
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no |
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Call Number |
DAG @ dag @ ABG2009 |
Serial |
1216 |
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Author |
Arnau Ramisa; Adriana Tapus; David Aldavert; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
Robust Vision-Based Localization using Combinations of Local Feature Regions Detectors |
Type |
Journal Article |
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Year |
2009 |
Publication |
Autonomous Robots |
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AR |
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Volume |
27 |
Issue |
4 |
Pages |
373-385 |
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This paper presents a vision-based approach for mobile robot localization. The model of the environment is topological. The new approach characterizes a place using a signature. This signature consists of a constellation of descriptors computed over different types of local affine covariant regions extracted from an omnidirectional image acquired rotating a standard camera with a pan-tilt unit. This type of representation permits a reliable and distinctive environment modelling. Our objectives were to validate the proposed method in indoor environments and, also, to find out if the combination of complementary local feature region detectors improves the localization versus using a single region detector. Our experimental results show that if false matches are effectively rejected, the combination of different covariant affine region detectors increases notably the performance of the approach by combining the different strengths of the individual detectors. In order to reduce the localization time, two strategies are evaluated: re-ranking the map nodes using a global similarity measure and using standard perspective view field of 45°.
In order to systematically test topological localization methods, another contribution proposed in this work is a novel method to see the degradation in localization performance as the robot moves away from the point where the original signature was acquired. This allows to know the robustness of the proposed signature. In order for this to be effective, it must be done in several, variated, environments that test all the possible situations in which the robot may have to perform localization. |
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0929-5593 |
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ADAS |
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no |
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Call Number |
Admin @ si @ RTA2009 |
Serial |
1245 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Seal detection and recognition: An approach for document indexing |
Type |
Conference Article |
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Year |
2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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Volume |
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Pages |
101–105 |
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Abstract |
Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RPL2009b |
Serial |
1239 |
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Permanent link to this record |
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Author |
Daniel Ponsa; Antonio Lopez |
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Title |
Seguimiento Visual de Contornos Computerizado |
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Miscellaneous |
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Year |
2009 |
Publication |
UAB Divulga, Revista de divulgacion cientifica |
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spreading;ADAS |
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no |
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ADAS @ adas @ PoL2009b |
Serial |
1270 |
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Author |
Josep M. Gonfaus |
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Title |
Semantic Segmentation of Images Using Random Ferns |
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Report |
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Year |
2009 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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Volume |
132 |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Place of Publication |
Bellaterra, Barcelona |
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ISE |
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no |
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Call Number |
Admin @ si @ Gon2009 |
Serial |
2391 |
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Permanent link to this record |
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Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
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Title |
Separability of Ternary Codes for Sparse Designs of Error-Correcting Output Codes |
Type |
Journal Article |
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Year |
2009 |
Publication |
Pattern Recognition Letters |
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PRL |
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Volume |
30 |
Issue |
3 |
Pages |
285–297 |
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Abstract |
Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework. Based on the new measure, we stress on how to design coding matrices preventing codification ambiguity and propose a new Sparse Random coding matrix with ternary distance maximization. The results on the UCI Repository and in a real speed traffic categorization problem show that when the coding design satisfies the new ternary measures, significant performance improvement is obtained independently of the decoding strategy applied. |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ EPR2009a |
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1153 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach |
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Conference Article |
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Year |
2009 |
Publication |
IEEE Workshop on Applications of Computer Vision |
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This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. |
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Utah, USA |
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1550-5790 |
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978-1-4244-5497-6 |
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WACV |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ DoR2009b |
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1256 |
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Author |
Mikhail Mozerov; Ariel Amato; Xavier Roca; Jordi Gonzalez |
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Title |
Solving the Multi Object Occlusion Problem in a Multiple Camera Tracking System |
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2009 |
Publication |
Pattern Recognition and Image Analysis |
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19 |
Issue |
1 |
Pages |
165-171 |
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An efficient method to overcome adverse effects of occlusion upon object tracking is presented. The method is based on matching paths of objects in time and solves a complex occlusion-caused problem of merging separate segments of the same path. |
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1054-6618 |
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ISE |
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no |
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ISE @ ise @ MAR2009a |
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1160 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
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Conference Article |
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2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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La Rochelle; France; July 2009 |
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GREC |
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DAG |
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DAG @ dag @ MSL2009a |
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1441 |
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Author |
Jose Antonio Rodriguez |
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Title |
Statistical frameworks and prior information modeling in handwritten word-spotting |
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Book Whole |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Handwritten word-spotting (HWS) is the pattern analysis task that consists in finding keywords in handwritten document images. So far, HWS has been applied mostly to historical documents in order to build search engines for such image collections. This thesis addresses the problem of word-spotting for detecting important keywords in business documents. This is a first step towards the process of automatic routing of correspondence based on content.
However, the application of traditional HWS techniques fails for this type of documents. As opposed to historical documents, real business documents present a very high variability in terms of writing styles, spontaneous writing, crossed-out words, spelling mistakes, etc. The main goal of this thesis is the development of pattern recognition techniques that lead to a high-performance HWS system for this challenging type of data.
We develop a statistical framework in which word models are expressed in terms of hidden Markov models and the a priori information is encoded in a universal vocabulary of Gaussian codewords. This systems leads to a very robust performance in word-spotting task. We also find that by constraining the word models to the universal vocabulary, the a priori information of the problem of interest can be exploited for developing new contributions. These include a novel writer adaptation method, a system for searching handwritten words by generating typed text images, and a novel model-based similarity between feature vector sequences. |
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Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Gemma Sanchez;Josep Llados;Florent Perronnin |
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no |
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Admin @ si @ Rod2009 |
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1266 |
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Author |
Jaume Garcia |
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Title |
Statistical Models of the Architecture and Function of the Left Ventricle |
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Book Whole |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Cardiovascular Diseases, specially those affecting the Left Ventricle (LV), are the leading cause of death in developed countries with approximately a 30% of all global deaths. In order to address this public health concern, physicians focus on diagnosis and therapy planning. On one hand, early and accurate detection of Regional Wall Motion Abnormalities (RWMA) significantly contributes to a quick diagnosis and prevents the patient to reach more severe stages. On the other hand, a thouroughly knowledge of the normal gross anatomy of the LV, as well as, the distribution of its muscular fibers is crucial for designing specific interventions and therapies (such as pacemaker implanction). Statistical models obtained from the analysis of different imaging modalities allow the computation of the normal ranges of variation within a given population. Normality models are a valuable tool for the definition of objective criterions quantifying the degree of (anomalous) deviation of the LV function and anatomy for a given subject. The creation of statistical models involve addressing three main issues: extraction of data from images, definition of a common domain for comparison of data across patients and designing appropriate statistical analysis schemes. In this PhD thesis we present generic image processing tools for the creation of statistical models of the LV anatomy and function. On one hand, we use differential geometry concepts to define a computational framework (the Normalized Parametric Domain, NPD) suitable for the comparison and fusion of several clinical scores obtained over the LV. On the other hand, we present a variational approach (the Harmonic Phase Flow, HPF) for the estimation of myocardial motion that provides dense and continuous vector fields without overestimating motion at injured areas. These tools are used for the creation of statistical models. Regarding anatomy, we obtain an atlas jointly modelling, both, LV gross anatomy and fiber architecture. Regarding function, we compute normality patterns of scores characterizing the (global and local) LV function and explore, for the first time, the configuration of local scores better suited for RWMA detection. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Debora Gil |
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IAM |
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Call Number |
IAM @ iam @ Gar2009a |
Serial |
1499 |
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Permanent link to this record |
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Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-Preserving Smoothing of Biomedical Images |
Type |
Conference Article |
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Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
5702 |
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Pages |
427-434 |
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Keywords |
non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. |
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Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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Address |
Münster, Germany |
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Publisher |
Springer Berlin Heidelberg |
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ISSN |
0302-9743 |
ISBN |
978-3-642-03766-5 |
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Conference |
CAIP |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ GHB2009 |
Serial |
1527 |
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Permanent link to this record |
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Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
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Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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Abstract |
In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
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Address |
La Rochelle; July 2009 |
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Conference |
GREC |
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Notes |
DAG |
Approved |
no |
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Call Number |
DAG @ dag @ RBO2009 |
Serial |
1444 |
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Permanent link to this record |