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Author | David Aldavert | ||||
Title | Visual Simultaneous Localization and Mapping | Type | Report | ||
Year | 2006 | Publication | CVC Technical Report #98 | Abbreviated Journal | |
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Address | CVC (UAB) | ||||
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Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ Ald2006 | Serial | 736 | ||
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Author | David Geronimo | ||||
Title | Model Features and Horizon Line Estimation for Pedestrian Detection in Advanced Driver Assistance Systems | Type | Report | ||
Year | 2006 | Publication | CVC Technical Report #98 | Abbreviated Journal | |
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Address | CVC (UAB) | ||||
Corporate Author | Thesis | Master's thesis | |||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ Ger2006 | Serial | 737 | ||
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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 | German Ros; J. Guerrero; Angel Sappa; Daniel Ponsa; Antonio Lopez | ||||
Title | Fast and Robust l1-averaging-based Pose Estimation for Driving Scenarios | Type | Conference Article | ||
Year | 2013 | Publication | 24th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | SLAM | ||||
Abstract | 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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Address | Bristol; UK; September 2013 | ||||
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Area | Expedition | Conference | BMVC | ||
Notes | ADAS | Approved | no | ||
Call Number | Admin @ si @ RGS2013b; ADAS @ adas @ | Serial | 2274 | ||
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Author | Jaume Amores | ||||
Title | MILDE: multiple instance learning by discriminative embedding | Type | Journal Article | ||
Year | 2015 | Publication | Knowledge and Information Systems | Abbreviated Journal | KAIS |
Volume | 42 | Issue | 2 | Pages | 381-407 |
Keywords | Multi-instance learning; Codebook; Bag of words | ||||
Abstract | While the objective of the standard supervised learning problem is to classify feature vectors, in the multiple instance learning problem, the objective is to classify bags, where each bag contains multiple feature vectors. This represents a generalization of the standard problem, and this generalization becomes necessary in many real applications such as drug activity prediction, content-based image retrieval, and others. While the existing paradigms are based on learning the discriminant information either at the instance level or at the bag level, we propose to incorporate both levels of information. This is done by defining a discriminative embedding of the original space based on the responses of cluster-adapted instance classifiers. Results clearly show the advantage of the proposed method over the state of the art, where we tested the performance through a variety of well-known databases that come from real problems, and we also included an analysis of the performance using synthetically generated data. | ||||
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Publisher | Springer London | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 0219-1377 | ISBN ![]() |
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Notes | ADAS; 601.042; 600.057; 600.076 | Approved | no | ||
Call Number | Admin @ si @ Amo2015 | Serial | 2383 | ||
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Author | Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik | ||||
Title | Asymmetric Distances for Binary Embeddings | Type | Journal Article | ||
Year | 2014 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
Volume | 36 | Issue | 1 | Pages | 33-47 |
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Abstract | In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques. | ||||
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ISSN | 0162-8828 | ISBN ![]() |
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Notes | DAG; 600.045; 605.203; 600.077 | Approved | no | ||
Call Number | Admin @ si @ GPG2014 | Serial | 2272 | ||
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Author | Karla Lizbeth Caballero; Joel Barajas; Oriol Pujol; J. Mauri; Petia Radeva | ||||
Title | Using Radio Frequency Reconstructed IVUS Images in Tissue Classification | Type | Miscellaneous | ||
Year | 2006 | Publication | Computers in Cardiology (CiC´06), 33: 533–536 | Abbreviated Journal | |
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Address | Valencia (Spain) | ||||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ CBP2006a | Serial | 761 | ||
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Author | David Rotger; Petia Radeva; Oriol Rodriguez | ||||
Title | Vessel Tortuosity Extraction from IVUS Images | Type | Miscellaneous | ||
Year | 2006 | Publication | Computers in Cardiology (CiC´06), 33: 689–692 | Abbreviated Journal | |
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Address | Valencia (Spain) | ||||
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Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ RRR2006 | Serial | 762 | ||
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Author | Dani Rowe | ||||
Title | Towards Robust Multiple-People Tracking in Unconstrained Environments | Type | Report | ||
Year | 2007 | Publication | CVC Technical Report #100 | Abbreviated Journal | |
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Address | CVC (UAB) | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Row2007 | Serial | 765 | ||
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Author | Ellen J.L. Brunenberg; Oriol Pujol; Bart M. Ter Haar Romeny; Petia Radeva | ||||
Title | Automatic IVUS Segmentation of Atherosclerotic Plaque with Stop & Go Snake | Type | Miscellaneous | ||
Year | 2006 | Publication | 9th International Conference on Medical Image Computing and Computer–Assisted Intervention (MICCAI´06), 9–16 | Abbreviated Journal | |
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Address | Copenhagen (Denmark) | ||||
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ BPT2006 | Serial | 767 | ||
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Author | Joaquin Salas; P. Martinez; Jordi Gonzalez | ||||
Title | Background Updating with the Use of Intrinsic Curves | Type | Book Chapter | ||
Year | 2006 | Publication | International Conference on Image Analysis and Recognition (ICIAR´06), LNCS 4141 (A. Campilho et al., eds.), 1: 731–742, ISBN 978–3–540–44891–4 | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | ISE @ ise @ SMG2006 | Serial | 768 | ||
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Author | Dani Rowe; I. Reid; Jordi Gonzalez; Juan J. Villanueva | ||||
Title | Unconstrained Multiple-People Tracking | Type | Book Chapter | ||
Year | 2006 | Publication | 28th Annual Symposium of the German Association for Pattern Recognition, LNCS 4174: 505–514, ISBN 978–3–540–44412–1 | Abbreviated Journal | |
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Address | Berlin (Germany) | ||||
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Notes | Approved | no | |||
Call Number | ISE @ ise @ RRG2006 | Serial | 769 | ||
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Author | Ignasi Rius; Javier Varona; Jordi Gonzalez; Juan J. Villanueva | ||||
Title | Action Spaces for Efficient Bayesian Tracking of Human Motion | Type | Miscellaneous | ||
Year | 2006 | Publication | International Conference on Pattern Recognition (ICPR´06), 1: 472–475 | Abbreviated Journal | |
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Address | Hong Kong (China) | ||||
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Notes | Approved | no | |||
Call Number | ISE @ ise @ RVG2006 | Serial | 770 | ||
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Author | Francisco Javier Orozco; F.A. Garcia; J.L. Arcos; Jordi Gonzalez | ||||
Title | Spatio-Temporal Reasoning for Reliable Facial Expression Interpretation | Type | Conference Article | ||
Year | 2007 | Publication | Proceedings of the 5th International Conference on Computer Vision Systems | Abbreviated Journal | |
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Address | Bielefeld University (Germany) | ||||
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Area | Expedition | Conference | ICVS | ||
Notes | ISE | Approved | no | ||
Call Number | ISE @ ise @ OGA2007 | Serial | 772 | ||
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Author | Francisco Javier Orozco; Jordi Gonzalez; Ignasi Rius; Xavier Roca | ||||
Title | Hierarchical Eyelid and Face Tracking | Type | Book Chapter | ||
Year | 2007 | Publication | 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:499–506 | Abbreviated Journal | |
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Address | Girona (Spain) | ||||
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Notes | ISE | Approved | no | ||
Call Number | ISE @ ise @ OGR2007 | Serial | 773 | ||
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