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Author |
Fernando Vilariño |
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Title |
A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy |
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2006 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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CVC (UAB) |
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Ph.D. thesis |
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Petia Radeva |
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84-933652-7-0 |
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800 |
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MV;SIAI |
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Admin @ si @ Vil2006; IAM @ iam @ Vil2006 |
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738 |
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Author |
Josep Llados |
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Title |
Computer Vision: Progress of Research and Development |
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2006 |
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1st CVC Internal Workshop Computer Vision: Progress of Research and Development, |
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J. Llados (ed.), |
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84-933652-8-9 |
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CVCRD |
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DAG @ dag @ Lla2006b |
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766 |
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Author |
F. Pla; Petia Radeva; Jordi Vitria |
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Title |
Pattern Recognition: Progress, Directions and Applications |
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2006 |
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84-933652-6-2 |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ PRV2006b |
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771 |
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Author |
W. Liu; Josep Llados |
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Title |
Graphics Recognition. Ten Years Review and Future Perspectives |
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Year |
2006 |
Publication |
6th International Workshop |
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3926 |
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Hong Kong (China) |
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GREC |
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DAG |
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no |
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DAG @ dag @ LiL2006 |
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800 |
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Author |
Josep Llados; W. Liu; Jean-Marc Ogier |
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Title |
Seventh IAPR International Workshop on Graphics Recognition GREC 2007 |
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2007 |
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Curitiba (Brazil) |
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DAG @ dag @ LLO2007 |
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835 |
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Author |
Joan Marti; Jose Miguel Benedi; Ana Maria Mendonça; Joan Serrat |
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Title |
Pattern Recognition and Image Analysis |
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Year |
2007 |
Publication |
3rd Iberian Conference |
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6669 |
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4477-4478 |
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Girona (Spain) |
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IbPRIA |
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ADAS |
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no |
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ADAS @ adas @ MBM2007 |
Serial |
994 |
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Author |
Jordi Gonzalez; Thomas B. Moeslund |
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Title |
Tracking Humans for the Evaluation of their Motion in Image Sequences |
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2008 |
Publication |
First International Workshop, THEMIS |
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Leeds (UK) |
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978-84-935251-9-4 |
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THEMIS |
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no |
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Call Number |
ISE @ ise @ GMW2008 |
Serial |
1002 |
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Author |
Juan J. Villanueva |
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Title |
Visualization, Imaging, and Image Processing, |
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2008 |
Publication |
Proceedings of the Eight IASTED International Conference |
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Palma de Mallorca (Spain) |
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978-0-88986-759-8 |
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no |
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ISE @ ise @ Vil2008 |
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1003 |
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Author |
Liu Wenyin; Josep Llados; Jean-Marc Ogier |
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Title |
Graphics Recognition. Recent Advances and New Opportunities. |
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2008 |
Publication |
7th International Workshop, Selected Papers, |
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5046 |
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Curitiba (Brazil) |
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LNCS |
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978-3-540-88184-1 |
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GREC |
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DAG |
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DAG @ dag @ WLO2008 |
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1012 |
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Author |
Alfons Juan-Ciscar; Gemma Sanchez |
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Title |
PRIS 2008. Pattern Recognition in Information Systems. Proceedings of the 8th international Workshop on Pattern Recognition in Information systems – PRIS 2008, in conjunction with ICEIS 2008 |
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2008 |
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Barcelona (Spain) |
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DAG |
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DAG @ dag @ JuS2008 |
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1054 |
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Author |
Miquel Ferrer |
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Title |
Theory and Algorithms on the Median Graph. Application to Graph-based Classification and Clustering |
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Year |
2008 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Ph.D. thesis |
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Francesc Serratosa Casanelles;Ernest Valveny |
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978-84-935251-7-0 |
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Admin @ si @ Fer2008 |
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1105 |
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Author |
Daniel Ponsa |
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Title |
Model-Based Visual Localisation of Contours and Vehicles |
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2007 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Phd Thesis |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Antonio Lopez;Xavier Roca |
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978-84-935251-3-2 |
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ADAS @ adas @ Pon2007 |
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1107 |
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Author |
Robert Benavente |
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Title |
A Parametric Model for Computational Colour Naming |
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2007 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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PhD Thesis |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Maria Vanrell |
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CIC |
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CAT @ cat @ Ben2007 |
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1108 |
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Author |
Robert Benavente; Laura Igual; Fernando Vilariño |
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Title |
Current Challenges in Computer Vision |
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2008 |
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Proccedings of the Third Internal Workshop |
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978-84-936529-0-6 |
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CVCRD |
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MILAB;CIC;SIAI |
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BCNPCL @ bcnpcl @ BIV2008 |
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1110 |
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Author |
Pau Baiget |
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Title |
Modeling Human Behavior for Image Sequence Understanding and Generation |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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Bellaterra (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Jordi Gonzalez;Xavier Roca |
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Admin @ si @ Bai2009 |
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1210 |
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