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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
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Title |
Cool world: domain adaptation of virtual and real worlds for human detection using active learning |
Type |
Conference Article |
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Year |
2011 |
Publication |
NIPS Domain Adaptation Workshop: Theory and Application |
Abbreviated Journal |
NIPS-DA |
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Volume |
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Issue |
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Pages |
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Keywords |
Pedestrian Detection; Virtual; Domain Adaptation; Active Learning |
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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. |
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Address |
Granada, Spain |
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Place of Publication |
Granada, Spain |
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Language |
English |
Summary Language |
English |
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DA-NIPS |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ VLP2011b |
Serial |
1756 |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Opponent Colors for Human Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
6669 |
Issue |
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Pages |
363-370 |
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Keywords |
Pedestrian Detection; Color; Part Based Models |
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Abstract |
Human detection is a key component in fields such as advanced driving assistance and video surveillance. However, even detecting non-occluded standing humans remains a challenge of intensive research. Finding good features to build human models for further detection is probably one of the most important issues to face. Currently, shape, texture and motion features have deserve extensive attention in the literature. However, color-based features, which are important in other domains (e.g., image categorization), have received much less attention. In fact, the use of RGB color space has become a kind of choice by default. The focus has been put in developing first and second order features on top of RGB space (e.g., HOG and co-occurrence matrices, resp.). In this paper we evaluate the opponent colors (OPP) space as a biologically inspired alternative for human detection. In particular, by feeding OPP space in the baseline framework of Dalal et al. for human detection (based on RGB, HOG and linear SVM), we will obtain better detection performance than by using RGB space. This is a relevant result since, up to the best of our knowledge, OPP space has not been previously used for human detection. This suggests that in the future it could be worth to compute co-occurrence matrices, self-similarity features, etc., also on top of OPP space, i.e., as we have done with HOG in this paper. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
J. Vitria; J.M. Sanches; M. Hernandez |
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Language |
English |
Summary Language |
English |
Original Title |
Opponent Colors for Human Detection |
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Series Title |
Lecture Notes on Computer Science |
Abbreviated Series Title |
LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ RVL2011a |
Serial |
1666 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE International Conference on Computer Vision – Workshops |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
2042-2049 |
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Keywords |
IEEE International Conference on Computer Vision – Workshops |
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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) |
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Language |
English |
Summary Language |
English |
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Conference |
ICCVW |
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Notes |
IAM; ADAS |
Approved |
no |
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Call Number |
IAM @ iam @ MGH2011 |
Serial |
1682 |
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Author |
Yainuvis Socarras; Sebastian Ramos; David Vazquez; Antonio Lopez; Theo Gevers |
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Title |
Adapting Pedestrian Detection from Synthetic to Far Infrared Images |
Type |
Conference Article |
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Year |
2013 |
Publication |
ICCV Workshop on Visual Domain Adaptation and Dataset Bias |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
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Keywords |
Domain Adaptation; Far Infrared; Pedestrian Detection |
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Abstract |
We present different techniques to adapt a pedestrian classifier trained with synthetic images and the corresponding automatically generated annotations to operate with far infrared (FIR) images. The information contained in this kind of images allow us to develop a robust pedestrian detector invariant to extreme illumination changes. |
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Address |
Sydney; Australia; December 2013 |
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Place of Publication |
Sydney, Australy |
Editor |
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Language |
English |
Summary Language |
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Original Title |
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Conference |
ICCVW-VisDA |
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Notes |
ADAS; 600.054; 600.055; 600.057; 601.217;ISE |
Approved |
no |
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Call Number |
ADAS @ adas @ SRV2013 |
Serial |
2334 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
7324 |
Issue |
I |
Pages |
184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Abstract |
Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Address |
Aveiro, Portugal |
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Thesis |
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Publisher |
Springer-Verlag Berlin Heidelberg |
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Language |
english |
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Series Editor |
Campilho, Aurélio and Kamel, Mohamed |
Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31294-6 |
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Conference |
ICIAR |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ MGH2012a |
Serial |
1899 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa; Javier Marin |
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Title |
Virtual Worlds and Active Learning for Human Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
13th International Conference on Multimodal Interaction |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
393-400 |
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Keywords |
Pedestrian Detection; Human detection; Virtual; Domain Adaptation; Active Learning |
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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. |
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Address |
Alicante, Spain |
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Corporate Author |
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Thesis |
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Publisher |
ACM DL |
Place of Publication |
New York, NY, USA, USA |
Editor |
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Language |
English |
Summary Language |
English |
Original Title |
Virtual Worlds and Active Learning for Human Detection |
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Series Editor |
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Series Title |
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Series Volume |
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Edition |
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ISSN |
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ISBN |
978-1-4503-0641-6 |
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Conference |
ICMI |
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Notes |
ADAS |
Approved |
yes |
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Call Number |
ADAS @ adas @ VLP2011a |
Serial |
1683 |
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Author |
Debora Gil; Agnes Borras; Manuel Ballester; Francesc Carreras; Ruth Aris; Manuel Vazquez; Enric Marti; Ferran Poveda |
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Title |
MIOCARDIA: Integrating cardiac function and muscular architecture for a better diagnosis |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Symposium on Applied Sciences in Biomedical and Communication Technologies |
Abbreviated Journal |
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Volume |
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Issue |
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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. |
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Address |
Barcelona; Spain |
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Corporate Author |
Association for Computing Machinery |
Thesis |
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Publisher |
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Place of Publication |
Barcelona, Spain |
Editor |
Association for Computing Machinery |
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Language |
english |
Summary Language |
english |
Original Title |
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Series Editor |
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ISBN |
978-1-4503-0913-4 |
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Conference |
ISABEL |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ GGB2011 |
Serial |
1691 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Assessing agonist efficacy in an uncertain Em world |
Type |
Conference Article |
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Year |
2012 |
Publication |
40th Keystone Symposia on mollecular and celular biology |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
79 |
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Keywords |
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Abstract |
The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed. |
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Address |
Fairmont Banff Springs, Banff, Alberta, Canada |
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Corporate Author |
Keystone Symposia |
Thesis |
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Publisher |
Keystone Symposia |
Place of Publication |
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Editor |
A. Christopoulus and M. Bouvier |
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Language |
english |
Summary Language |
english |
Original Title |
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Series Editor |
Keystone Symposia |
Series Title |
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Edition |
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Conference |
KSMCB |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ RGG2012 |
Serial |
1855 |
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