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| Author | Ricardo Toledo | ||||
| Title | Cardiac workstation and dynamic model to assist in coronary tree analysis. | Type | Book Whole | ||
| Year | 2001 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | Petia Radeva;JuanJose Villanueva | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | Admin @ si @ Tol2001 | Serial | 166 | ||
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| Author | Antonio Lopez | ||||
| Title | Multilocal Methods for Ridge and Valley Delineation in Image Analysis. | Type | Book Whole | ||
| Year | 2000 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | Joan Serrat | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ Lop2000 | Serial | 174 | ||
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| Author | A. Pujol | ||||
| Title | Contributions to shape and texture face similarity measurement. | Type | Book Whole | ||
| Year | 2001 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | JuanJose Villanueva | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Puj2001 | Serial | 202 | ||
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| Author | David Lloret | ||||
| Title | Medical Image Registration Based on a Creaseress Measure. | Type | Book Whole | ||
| Year | 2002 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | Joan Serrat | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Llo2002 | Serial | 321 | ||
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| Author | Jordi Gonzalez | ||||
| Title | Human Sequence Evaluation: the Key-frame Approach | Type | Book Whole | ||
| Year | 2004 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | Xavier Roca;Javier Varona | ||
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| Notes | Approved | no | |||
| Call Number | ISE @ ise @ Gon2004 | Serial | 362 | ||
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| Author | David Guillamet | ||||
| Title | Statistical Local Appearance Models for Object Recognition | Type | Book Whole | ||
| Year | 2004 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Address | Bellaterra | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Jordi Vitria | ||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Gui2004 | Serial | 444 | ||
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| Author | Oriol Pujol | ||||
| Title | A semi-Supervised Statistical Framework and Generative Snakes for IVUS Analysis | Type | Book Whole | ||
| Year | 2004 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Address | CVC (UAB), Bellaterra | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Petia Radeva | ||
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| Notes | HuPBA;MILAB | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ Puj2004 | Serial | 512 | ||
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| Author | David Masip | ||||
| Title | Face Classification Using Discriminative Features and Classifier Combination | Type | Book Whole | ||
| Year | 2005 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Jordi Vitria | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 84-933652-3-8 | Medium | ||
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| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ Mas2005b | Serial | 602 | ||
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| Author | Misael Rosales | ||||
| Title | A Physics-Based Image Modelling of IVUS as a Geometric and Kinematic System | Type | Book Whole | ||
| Year | 2005 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Petia Radeva | ||
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| Area | Expedition | 978-84-922529-8-7 | Conference | ||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ Ros2005 | Serial | 603 | ||
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| Author | Fernando Vilariño | ||||
| Title | A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy | Type | Book Whole | ||
| Year | 2006 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions obtained by labelling all the motility events present in a video provided by a capsule with a wireless micro-camera, which is ingested by the patient. However, the visual analysis of these video sequences presents several im- portant drawbacks, mainly related to both the large amount of time needed for the visualization process, and the low prevalence of intestinal contractions in video.
In this work we propose a machine learning system to automatically detect the intestinal contractions in video capsule endoscopy, driving a very useful but not fea- sible clinical routine into a feasible clinical procedure. Our proposal is divided into two different parts: The first part tackles the problem of the automatic detection of phasic contractions in capsule endoscopy videos. Phasic contractions are dynamic events spanning about 4-5 seconds, which show visual patterns with a high variability. Our proposal is based on a sequential design which involves the analysis of textural, color and blob features with powerful classifiers such as SVM. This approach appears to cope with two basic aims: the reduction of the imbalance rate of the data set, and the modular construction of the system, which adds the capability of including domain knowledge as new stages in the cascade. The second part of the current work tackles the problem of the automatic detection of tonic contractions. Tonic contrac- tions manifest in capsule endoscopy as a sustained pattern of the folds and wrinkles of the intestine, which may be prolonged for an undetermined span of time. Our proposal is based on the analysis of the wrinkle patterns, presenting a comparative study of diverse features and classification methods, and providing a set of appro- priate descriptors for their characterization. We provide a detailed analysis of the performance achieved by our system both in a qualitative and a quantitative way. |
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| Address | CVC (UAB) | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Place of Publication | Editor | Petia Radeva | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | 84-933652-7-0 | Edition | ||
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| Area | 800 | Expedition | Conference | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number | Admin @ si @ Vil2006; IAM @ iam @ Vil2006 | Serial | 738 | ||
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| Author | Aymen Azaza | ||||
| Title | Context, Motion and Semantic Information for Computational Saliency | Type | Book Whole | ||
| Year | 2018 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The main objective of this thesis is to highlight the salient object in an image or in a video sequence. We address three important—but in our opinion
insufficiently investigated—aspects of saliency detection. Firstly, we start by extending previous research on saliency which explicitly models the information provided from the context. Then, we show the importance of explicit context modelling for saliency estimation. Several important works in saliency are based on the usage of object proposals. However, these methods focus on the saliency of the object proposal itself and ignore the context. To introduce context in such saliency approaches, we couple every object proposal with its direct context. This allows us to evaluate the importance of the immediate surround (context) for its saliency. We propose several saliency features which are computed from the context proposals including features based on omni-directional and horizontal context continuity. Secondly, we investigate the usage of top-downmethods (high-level semantic information) for the task of saliency prediction since most computational methods are bottom-up or only include few semantic classes. We propose to consider a wider group of object classes. These objects represent important semantic information which we will exploit in our saliency prediction approach. Thirdly, we develop a method to detect video saliency by computing saliency from supervoxels and optical flow. In addition, we apply the context features developed in this thesis for video saliency detection. The method combines shape and motion features with our proposed context features. To summarize, we prove that extending object proposals with their direct context improves the task of saliency detection in both image and video data. Also the importance of the semantic information in saliency estimation is evaluated. Finally, we propose a newmotion feature to detect saliency in video data. The three proposed novelties are evaluated on standard saliency benchmark datasets and are shown to improve with respect to state-of-the-art. |
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| Address | October 2018 | ||||
| Corporate Author | Thesis |
Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Joost Van de Weijer;Ali Douik | |
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| ISSN | ISBN | 978-84-945373-9-4 | Medium | ||
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| Notes | LAMP; 600.120 | Approved | no | ||
| Call Number | Admin @ si @ Aza2018 | Serial | 3218 | ||
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| Author | Miquel Ferrer | ||||
| Title | Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering | Type | Book Whole | ||
| Year | 2008 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Publisher | Place of Publication | Editor | Francesc Serratosa Casanelles;Ernest Valveny | ||
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| Area | Expedition | 978-84-935251-7-0 | Conference | ||
| Notes | Approved | no | |||
| Call Number | Admin @ si @ Fer2008 | Serial | 1105 | ||
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| Author | Daniel Ponsa | ||||
| Title | Model-Based Visual Localisation of Contours and Vehicles | Type | Book Whole | ||
| Year | 2007 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Phd Thesis | ||||
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| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Antonio Lopez;Xavier Roca | |
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| ISSN | ISBN | 978-84-935251-3-2 | Medium | ||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ Pon2007 | Serial | 1107 | ||
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| Author | Robert Benavente | ||||
| Title | A Parametric Model for Computational Colour Naming | Type | Book Whole | ||
| Year | 2007 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Keywords | PhD Thesis | ||||
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| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell | |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ Ben2007 | Serial | 1108 | ||
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| Author | Pau Baiget | ||||
| Title | Modeling Human Behavior for Image Sequence Understanding and Generation | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | The comprehension of animal behavior, especially human behavior, is one of the most ancient and studied problems since the beginning of civilization. The big list of factors that interact to determine a person action require the collaboration of different disciplines, such as psichology, biology, or sociology. In the last years the analysis of human behavior has received great attention also from the computer vision community, given the latest advances in the acquisition of human motion data from image sequences.
Despite the increasing availability of that data, there still exists a gap towards obtaining a conceptual representation of the obtained observations. Human behavior analysis is based on a qualitative interpretation of the results, and therefore the assignment of concepts to quantitative data is linked to a certain ambiguity. This Thesis tackles the problem of obtaining a proper representation of human behavior in the contexts of computer vision and animation. On the one hand, a good behavior model should permit the recognition and explanation the observed activity in image sequences. On the other hand, such a model must allow the generation of new synthetic instances, which model the behavior of virtual agents. First, we propose methods to automatically learn the models from observations. Given a set of quantitative results output by a vision system, a normal behavior model is learnt. This results provides a tool to determine the normality or abnormality of future observations. However, machine learning methods are unable to provide a richer description of the observations. We confront this problem by means of a new method that incorporates prior knowledge about the enviornment and about the expected behaviors. This framework, formed by the reasoning engine FMTL and the modeling tool SGT allows the generation of conceptual descriptions of activity in new image sequences. Finally, we demonstrate the suitability of the proposed framework to simulate behavior of virtual agents, which are introduced into real image sequences and interact with observed real agents, thereby easing the generation of augmented reality sequences. The set of approaches presented in this Thesis has a growing set of potential applications. The analysis and description of behavior in image sequences has its principal application in the domain of smart video--surveillance, in order to detect suspicious or dangerous behaviors. Other applications include automatic sport commentaries, elderly monitoring, road traffic analysis, and the development of semantic video search engines. Alternatively, behavioral virtual agents allow to simulate accurate real situations, such as fires or crowds. Moreover, the inclusion of virtual agents into real image sequences has been widely deployed in the games and cinema industries. |
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| Address | Bellaterra (Spain) | ||||
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Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Jordi Gonzalez;Xavier Roca | |
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Bai2009 | Serial | 1210 | ||
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