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Author |
Francisco Javier Orozco; Pau Baiget; Jordi Gonzalez; Xavier Roca |
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Title |
Eyelids and Face Tracking in Real-Time |
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Miscellaneous |
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2006 |
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6th IASTED International Conference Visualization, Imaging, and Image Processing (VIIP´06), 165–170 |
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Palma de Mallorca (Spain) |
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ISE |
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ISE @ ise @ OBG2006 |
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730 |
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Author |
Salim Jouili; Salvatore Tabbone; Ernest Valveny |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Comparing Graph Similarity Measures for Graphical Recognition |
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Book Chapter |
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Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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37-48 |
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In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG |
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Admin @ si @ JTV2010 |
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2404 |
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Author |
Fadi Dornaika; Franck Davoine |
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Title |
On appearance based face and facial action tracking |
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2006 |
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IEEE Transactions on Circuits and Systems for Video Technology, 16(9): 1838–1853 |
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Admin @ si @ DoD2006b |
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732 |
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Author |
Fadi Dornaika; J. Ahlberg |
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Title |
Fitting 3D face models for tracking and active appearance model training |
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2006 |
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Image and Vision Computing, 24(9): 1010–1024 |
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Admin @ si @ DoA2006 |
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733 |
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Author |
Fadi Dornaika; Franck Davoine |
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Title |
Facial expression recognition using auto-regressive models |
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Miscellaneous |
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Year |
2006 |
Publication |
18th International Conference on Pattern Recognition (ICPR´06), ISBN: 0–7695–2521–0, 4: 520–523 |
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Hong Kong |
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Admin @ si @ DoD2006a |
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734 |
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Author |
R. Herault; Franck Davoine; Fadi Dornaika; Y. Grandvalet |
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Title |
Simultaneous and robust face and facial action tracking |
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Miscellaneous |
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2006 |
Publication |
15eme Congres Francophone AFRIF–AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA´06) |
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Tours (France) |
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Admin @ si @ HDD2006 |
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735 |
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Author |
David Aldavert |
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Title |
Visual Simultaneous Localization and Mapping |
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Report |
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2006 |
Publication |
CVC Technical Report #98 |
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CVC (UAB) |
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ADAS |
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no |
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Admin @ si @ Ald2006 |
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736 |
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Author |
David Geronimo |
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Title |
Model Features and Horizon Line Estimation for Pedestrian Detection in Advanced Driver Assistance Systems |
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Report |
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2006 |
Publication |
CVC Technical Report #98 |
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CVC (UAB) |
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Master's thesis |
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ADAS |
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ADAS @ adas @ Ger2006 |
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737 |
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Author |
Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
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Title |
A Machine Learning Approach for Intestinal Motility Assessment with Capsule Endoscopy |
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Year |
2006 |
Publication |
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 |
German Ros; J. Guerrero; Angel Sappa; Daniel Ponsa; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Fast and Robust l1-averaging-based Pose Estimation for Driving Scenarios |
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Conference Article |
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2013 |
Publication |
24th British Machine Vision Conference |
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SLAM |
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Robust visual pose estimation is at the core of many computer vision applications, being fundamental for Visual SLAM and Visual Odometry problems. During the last decades, many approaches have been proposed to solve these problems, being RANSAC one of the most accepted and used. However, with the arrival of new challenges, such as large driving scenarios for autonomous vehicles, along with the improvements in the data gathering frameworks, new issues must be considered. One of these issues is the capability of a technique to deal with very large amounts of data while meeting the realtime
constraint. With this purpose in mind, we present a novel technique for the problem of robust camera-pose estimation that is more suitable for dealing with large amount of data, which additionally, helps improving the results. The method is based on a combination of a very fast coarse-evaluation function and a robust ℓ1-averaging procedure. Such scheme leads to high-quality results while taking considerably less time than RANSAC.
Experimental results on the challenging KITTI Vision Benchmark Suite are provided, showing the validity of the proposed approach. |
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Bristol; UK; September 2013 |
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BMVC |
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ADAS |
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Admin @ si @ RGS2013b; ADAS @ adas @ |
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2274 |
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Author |
Karla Lizbeth Caballero; Joel Barajas; Oriol Pujol; J. Mauri; Petia Radeva |
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Title |
Using Radio Frequency Reconstructed IVUS Images in Tissue Classification |
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Miscellaneous |
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2006 |
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Computers in Cardiology (CiC´06), 33: 533–536 |
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Valencia (Spain) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ CBP2006a |
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761 |
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Author |
David Rotger; Petia Radeva; Oriol Rodriguez |
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Title |
Vessel Tortuosity Extraction from IVUS Images |
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Miscellaneous |
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2006 |
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Computers in Cardiology (CiC´06), 33: 689–692 |
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Valencia (Spain) |
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MILAB |
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BCNPCL @ bcnpcl @ RRR2006 |
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762 |
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Author |
Dani Rowe |
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Title |
Towards Robust Multiple-People Tracking in Unconstrained Environments |
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2007 |
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CVC Technical Report #100 |
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CVC (UAB) |
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Admin @ si @ Row2007 |
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765 |
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Author |
Josep Llados |
![find book details (via ISBN) isbn](img/isbn.gif)
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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 |
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DAG @ dag @ Lla2006b |
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766 |
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Author |
Ellen J.L. Brunenberg; Oriol Pujol; Bart M. Ter Haar Romeny; Petia Radeva |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Automatic IVUS Segmentation of Atherosclerotic Plaque with Stop & Go Snake |
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Miscellaneous |
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2006 |
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9th International Conference on Medical Image Computing and Computer–Assisted Intervention (MICCAI´06), 9–16 |
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Copenhagen (Denmark) |
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MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ BPT2006 |
Serial |
767 |
|
Permanent link to this record |