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| Author | Patricia Marquez; Debora Gil; Aura Hernandez-Sabate | ||||
| Title | A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth | Type | Conference Article | ||
| Year | 2011 | Publication  |
IEEE International Conference on Computer Vision – Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 2042-2049 | ||
| Keywords | IEEE International Conference on Computer Vision – Workshops | ||||
| Abstract | Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. | ||||
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| Publisher | IEEE | Place of Publication | Barcelona (Spain) | Editor | |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICCVW | ||
| Notes | IAM; ADAS | Approved | no | ||
| Call Number | IAM @ iam @ MGH2011 | Serial | 1682 | ||
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| Author | Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti | ||||
| Title | Multiscale Tractography for Representing Heart Muscular Architecture | Type | Conference Article | ||
| Year | 2011 | Publication |
In MICCAI 2011 Workshop on Computational Diffusion MRI | Abbreviated Journal | |
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| Abstract | Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | English | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CDRMI | ||
| Notes | IAM | Approved | no | ||
| Call Number | IAM @ iam @ PGA2011 | Serial | 1681 | ||
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| Author | Aura Hernandez-Sabate; Debora Gil | ||||
| Title | The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries | Type | Book Chapter | ||
| Year | 2012 | Publication |
Intravascular Ultrasound | Abbreviated Journal | |
| Volume | Issue | Pages | 185-206 | ||
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| Publisher | Intech | Place of Publication | Editor | Yasuhiro Honda | |
| Language | English | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-953-307-900-4 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM; ADAS | Approved | no | ||
| Call Number | IAM @ iam @ HeG2012 | Serial | 1684 | ||
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| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; David Geronimo | ||||
| Title | Interactive Training of Human Detectors | Type | Book Chapter | ||
| Year | 2013 | Publication |
Multiodal Interaction in Image and Video Applications | Abbreviated Journal | |
| Volume | 48 | Issue | Pages | 169-182 | |
| Keywords | Pedestrian Detection; Virtual World; AdaBoost; Domain Adaptation | ||||
| Abstract | Image based human detection remains as a challenging problem. Most promising detectors rely on classifiers trained with labelled samples. However, labelling is a manual labor intensive step. To overcome this problem we propose to collect images of pedestrians from a virtual city, i.e., with automatic labels, and train a pedestrian detector with them, which works fine when such virtual-world data are similar to testing one, i.e., real-world pedestrians in urban areas. When testing data is acquired in different conditions than training one, e.g., human detection in personal photo albums, dataset shift appears. In previous work, we cast this problem as one of domain adaptation and solve it with an active learning procedure. In this work, we focus on the same problem but evaluating a different set of faster to compute features, i.e., Haar, EOH and their combination. In particular, we train a classifier with virtual-world data, using such features and Real AdaBoost as learning machine. This classifier is applied to real-world training images. Then, a human oracle interactively corrects the wrong detections, i.e., few miss detections are manually annotated and some false ones are pointed out too. A low amount of manual annotation is fixed as restriction. Real- and virtual-world difficult samples are combined within what we call cool world and we retrain the classifier with this data. Our experiments show that this adapted classifier is equivalent to the one trained with only real-world data but requiring 90% less manual annotations. | ||||
| Address | Springer Heidelberg New York Dordrecht London | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1868-4394 | ISBN | 978-3-642-35931-6 | Medium | |
| Area | Expedition | Conference | |||
| Notes | ADAS; 600.057; 600.054; 605.203 | Approved | no | ||
| Call Number | VLP2013; ADAS @ adas @ vlp2013 | Serial | 2193 | ||
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| Author | David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin | ||||
| Title | Cool world: domain adaptation of virtual and real worlds for human detection using active learning | Type | Conference Article | ||
| Year | 2011 | Publication |
NIPS Domain Adaptation Workshop: Theory and Application | Abbreviated Journal | NIPS-DA |
| Volume | Issue | Pages | |||
| Keywords | Pedestrian Detection; Virtual; Domain Adaptation; Active Learning | ||||
| Abstract | Image based human detection is of paramount interest for different applications. The most promising human detectors rely on discriminatively learnt classifiers, i.e., trained with labelled samples. However, labelling is a manual intensive task, especially in cases like human detection where it is necessary to provide at least bounding boxes framing the humans for training. To overcome such problem, in Marin et al. we have proposed the use of a virtual world where the labels of the different objects are obtained automatically. This means that the human models (classifiers) are learnt using the appearance of realistic computer graphics. Later, these models are used for human detection in images of the real world. The results of this technique are surprisingly good. However, these are not always as good as the classical approach of training and testing with data coming from the same camera and the same type of scenario. Accordingly, in Vazquez et al. we cast the problem as one of supervised domain adaptation. In doing so, we assume that a small amount of manually labelled samples from real-world images is required. To collect these labelled samples we use an active learning technique. Thus, ultimately our human model is learnt by the combination of virtual- and real-world labelled samples which, to the best of our knowledge, was not done before. Here, we term such combined space cool world. In this extended abstract we summarize our proposal, and include quantitative results from Vazquez et al. showing its validity. | ||||
| Address | Granada, Spain | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Granada, Spain | Editor | ||
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | DA-NIPS | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ VLP2011b | Serial | 1756 | ||
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| Author | David Vazquez | ||||
| Title | Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection | Type | Book Whole | ||
| Year | 2013 | Publication |
PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
| Volume | 1 | Issue | 1 | Pages | 1-105 |
| Keywords | Pedestrian Detection; Domain Adaptation | ||||
| Abstract | Pedestrian detection is of paramount interest for many applications, e.g. Advanced Driver Assistance Systems, Intelligent Video Surveillance and Multimedia systems. Most promising pedestrian detectors rely on appearance-based classifiers trained with annotated data. However, the required annotation step represents an intensive and subjective task for humans, what makes worth to minimize their intervention in this process by using computational tools like realistic virtual worlds. The reason to use these kind of tools relies in the fact that they allow the automatic generation of precise and rich annotations of visual information. Nevertheless, the use of this kind of data comes with the following question: can a pedestrian appearance model learnt with virtual-world data work successfully for pedestrian detection in real-world scenarios?. To answer this question, we conduct different experiments that suggest a positive answer. However, the pedestrian classifiers trained with virtual-world data can suffer the so called dataset shift problem as real-world based classifiers does. Accordingly, we have designed different domain adaptation techniques to face this problem, all of them integrated in a same framework (V-AYLA). We have explored different methods to train a domain adapted pedestrian classifiers by collecting a few pedestrian samples from the target domain (real world) and combining them with many samples of the source domain (virtual world). The extensive experiments we present show that pedestrian detectors developed within the V-AYLA framework do achieve domain adaptation. Ideally, we would like to adapt our system without any human intervention. Therefore, as a first proof of concept we also propose an unsupervised domain adaptation technique that avoids human intervention during the adaptation process. To the best of our knowledge, this Thesis work is the first demonstrating adaptation of virtual and real worlds for developing an object detector. Last but not least, we also assessed a different strategy to avoid the dataset shift that consists in collecting real-world samples and retrain with them in such a way that no bounding boxes of real-world pedestrians have to be provided. We show that the generated classifier is competitive with respect to the counterpart trained with samples collected by manually annotating pedestrian bounding boxes. The results presented on this Thesis not only end with a proposal for adapting a virtual-world pedestrian detector to the real world, but also it goes further by pointing out a new methodology that would allow the system to adapt to different situations, which we hope will provide the foundations for future research in this unexplored area. | ||||
| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Barcelona | Editor | Antonio Lopez;Daniel Ponsa |
| Language | English | Summary Language | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-84-940530-1-6 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | adas | Approved | yes | ||
| Call Number | ADAS @ adas @ Vaz2013 | Serial | 2276 | ||
| Permanent link to this record | |||||
| Author | Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester | ||||
| Title | Multilocal Creaseness Measure | Type | Journal | ||
| Year | 2012 | Publication |
The Insight Journal | Abbreviated Journal | IJ |
| Volume | Issue | Pages | |||
| Keywords | Ridges, Valley, Creaseness, Structure Tensor, Skeleton, | ||||
| Abstract | This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission. | ||||
| Address | |||||
| Corporate Author | Alma IT Systems | Thesis | |||
| Publisher | Place of Publication | Editor | |||
| Language | english | Summary Language | english | Original Title | |
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | |||
| Notes | IAM;ADAS; | Approved | no | ||
| Call Number | IAM @ iam @ VGL2012 | Serial | 1840 | ||
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| Author | Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester | ||||
| Title | Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs | Type | Book Chapter | ||
| Year | 2012 | Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging | Abbreviated Journal | |
| Volume | 7029 | Issue | Pages | 223–230 | |
| Keywords | medial manifolds, abdomen. | ||||
| Abstract | Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. |
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| Address | Toronto; Canada; | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Link | Place of Publication | Berlin | Editor | H. Yoshida et al |
| Language | English | Summary Language | English | Original Title | |
| Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | LNCS | |
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-28556-1 | Medium | |
| Area | Expedition | Conference | ABDI | ||
| Notes | IAM;MV | Approved | no | ||
| Call Number | IAM @ iam @ VGB2012 | Serial | 1834 | ||
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