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Author | Muhammad Anwer Rao; David Vazquez; Antonio Lopez | ||||
Title | Color Contribution to Part-Based Person Detection in Different Types of Scenarios | Type | Conference Article | ||
Year | 2011 | Publication | 14th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
Volume | 6855 | Issue | II | Pages | 463-470 |
Keywords | Pedestrian Detection; Color | ||||
Abstract | Camera-based person detection is of paramount interest due to its potential applications. The task is diffcult because the great variety of backgrounds (scenarios, illumination) in which persons are present, as well as their intra-class variability (pose, clothe, occlusion). In fact, the class person is one of the included in the popular PASCAL visual object classes (VOC) challenge. A breakthrough for this challenge, regarding person detection, is due to Felzenszwalb et al. These authors proposed a part-based detector that relies on histograms of oriented gradients (HOG) and latent support vector machines (LatSVM) to learn a model of the whole human body and its constitutive parts, as well as their relative position. Since the approach of Felzenszwalb et al. appeared new variants have been proposed, usually giving rise to more complex models. In this paper, we focus on an issue that has not attracted suficient interest up to now. In particular, we refer to the fact that HOG is usually computed from RGB color space, but other possibilities exist and deserve the corresponding investigation. In this paper we challenge RGB space with the opponent color space (OPP), which is inspired in the human vision system.We will compute the HOG on top of OPP, then we train and test the part-based human classifer by Felzenszwalb et al. using PASCAL VOC challenge protocols and person database. Our experiments demonstrate that OPP outperforms RGB. We also investigate possible differences among types of scenarios: indoor, urban and countryside. Interestingly, our experiments suggest that the beneficts of OPP with respect to RGB mainly come for indoor and countryside scenarios, those in which the human visual system was designed by evolution. | ||||
Address | Seville, Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer | Place of Publication | Berlin Heidelberg | Editor | P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
Language | English | Summary Language | english | Original Title | Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-23677-8 | Medium | |
Area | Expedition | Conference | CAIP | ||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ RVL2011b | Serial | 1665 | ||
Permanent link to this record | |||||
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 | |
Volume | Issue | Pages | |||
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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 | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CDRMI | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ PGA2011 | Serial | 1681 | ||
Permanent link to this record | |||||
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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Corporate Author | Thesis | ||||
Publisher | IEEE | Place of Publication | Barcelona (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 | ICCVW | ||
Notes | IAM; ADAS | Approved | no | ||
Call Number | IAM @ iam @ MGH2011 | Serial | 1682 | ||
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Author | David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin | ||||
Title | Virtual Worlds and Active Learning for Human Detection | Type | Conference Article | ||
Year | 2011 | Publication | 13th International Conference on Multimodal Interaction | Abbreviated Journal | |
Volume | Issue | Pages | 393-400 | ||
Keywords | Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning | ||||
Abstract | Image based human detection is of paramount interest due to its potential applications in fields such as advanced driving assistance, surveillance and media analysis. However, even detecting non-occluded standing humans remains a challenge of intensive research. The most promising human detectors rely on classifiers developed in the discriminative paradigm, i.e., trained with labelled samples. However, labeling is a manual intensive step, 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, some authors 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 rendered images, i.e., using 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, or similar ones. Accordingly, in this paper we address the challenge of using a virtual world for gathering (while playing a videogame) a large amount of automatically labelled samples (virtual humans and background) and then training a classifier that performs equal, in real-world images, than the one obtained by equally training from manually labelled real-world samples. For doing that, we cast the problem as one of 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 propose a non-standard active learning technique. Therefore, ultimately our human model is learnt by the combination of virtual and real world labelled samples (Fig. 1), which has not been done before. We present quantitative results showing that this approach is valid. | ||||
Address | Alicante, Spain | ||||
Corporate Author | Thesis | ||||
Publisher | ACM DL | Place of Publication | New York, NY, USA, USA | Editor | |
Language | English | Summary Language | English | Original Title | Virtual Worlds and Active Learning for Human Detection |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4503-0641-6 | Medium | ||
Area | Expedition | Conference | ICMI | ||
Notes | ADAS | Approved | yes | ||
Call Number | ADAS @ adas @ VLP2011a | Serial | 1683 | ||
Permanent link to this record | |||||
Author | Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda | ||||
Title | MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis | Type | Conference Article | ||
Year | 2011 | Publication | 14th International Symposium on Applied Sciences in Biomedical and Communication Technologies | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. The MIOCARDIA project is a multidisciplinary project in cooperation with l'Hospital de la Santa Creu i de Sant Pau, Clinica la Creu Blanca and Barcelona Supercomputing Center. The ultimate goal of this project is defining a computational model of the myocardium. The model takes into account the deep interrelation between the anatomy and the mechanics of the heart. The paper explains the workflow of the MIOCARDIA project. It also introduces 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 provides evidences of a global helical organization. | ||||
Address | Barcelona; Spain | ||||
Corporate Author | Association for Computing Machinery | Thesis | |||
Publisher | Place of Publication | Barcelona, Spain | Editor | Association for Computing Machinery | |
Language | english | Summary Language | english | Original Title | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-4503-0913-4 | Medium | ||
Area | Expedition | Conference | ISABEL | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ GGB2011 | Serial | 1691 | ||
Permanent link to this record | |||||
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 | ||
Permanent link to this record | |||||
Author | Carles Sanchez | ||||
Title | Tracheal ring detection in bronchoscopy | Type | Report | ||
Year | 2011 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 168 | Issue | Pages | ||
Keywords | Bronchoscopy, tracheal ring, segmentation | ||||
Abstract | Endoscopy is the process in which a camera is introduced inside a human.
Given that endoscopy provides realistic images (in contrast to other modalities) and allows non-invase minimal intervention procedures (which can aid in diagnosis and surgical interventions), its use has spreaded during last decades. In this project we will focus on bronchoscopic procedures, during which the camera is introduced through the trachea in order to have a diagnostic of the patient. The diagnostic interventions are focused on: degree of stenosis (reduction in tracheal area), prosthesis or early diagnosis of tumors. In the first case, assessment of the luminal area and the calculation of the diameters of the tracheal rings are required. A main limitation is that all the process is done by hand, which means that the doctor takes all the measurements and decisions just by looking at the screen. As far as we know there is no computational framework for helping the doctors in the diagnosis. This project will consist of analysing bronchoscopic videos in order to extract useful information for the diagnostic of the degree of stenosis. In particular we will focus on segmentation of the tracheal rings. As a result of this project several strategies (for detecting tracheal rings) had been implemented in order to compare their performance. |
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Corporate Author | Thesis | Master's thesis | |||
Publisher | Place of Publication | Editor | Debora Gil, F.Javier Sanchez | ||
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;MV | Approved | no | ||
Call Number | IAM @ iam @ San2011 | Serial | 1841 | ||
Permanent link to this record | |||||
Author | Javier Marin; David Vazquez; David Geronimo; Antonio Lopez | ||||
Title | Learning Appearance in Virtual Scenarios for Pedestrian Detection | Type | Conference Article | ||
Year | 2010 | Publication | 23rd IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 137–144 | ||
Keywords | Pedestrian Detection; Domain Adaptation | ||||
Abstract | Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers trained with labelled samples. This paper addresses the following question: can a pedestrian appearance model learnt in virtual scenarios work successfully for pedestrian detection in real images? (Fig. 1). Our experiments suggest a positive answer, which is a new and relevant conclusion for research in pedestrian detection. More specifically, we record training sequences in virtual scenarios and then appearance-based pedestrian classifiers are learnt using HOG and linear SVM. We test such classifiers in a publicly available dataset provided by Daimler AG for pedestrian detection benchmarking. This dataset contains real world images acquired from a moving car. The obtained result is compared with the one given by a classifier learnt using samples coming from real images. The comparison reveals that, although virtual samples were not specially selected, both virtual and real based training give rise to classifiers of similar performance. | ||||
Address | San Francisco; CA; USA; June 2010 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | English | Summary Language | English | Original Title | Learning Appearance in Virtual Scenarios for Pedestrian Detection |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1063-6919 | ISBN | 978-1-4244-6984-0 | Medium | |
Area | Expedition | Conference | CVPR | ||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ MVG2010 | Serial | 1304 | ||
Permanent link to this record |