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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Vocabulary Selection for Graph of Words Embedding |
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 |
216-223 |
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Abstract |
The Graph of Words Embedding consists in mapping every graph in a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. It has been shown to perform well for graphs with discrete label alphabets. In this paper we extend the methodology to graphs with n-dimensional continuous attributes by selecting node representatives. We propose three different discretization procedures for the attribute space and experimentally evaluate the dependence on both the selector and the number of node representatives. In the context of graph classification, the experimental results reveal that on two out of three public databases the proposed extension achieves superior performance over a standard reference system. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Thesis |
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Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
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LNCS |
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ISSN |
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ISBN |
978-3-642-21256-7 |
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Conference |
IbPRIA |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
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Permanent link to this record |
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Author |
Jaume Gibert; Ernest Valveny; Oriol Ramos Terrades; Horst Bunke |
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Title |
Multiple Classifiers for Graph of Words Embedding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
36-45 |
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Keywords |
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Abstract |
During the last years, there has been an increasing interest in applying the multiple classifier framework to the domain of structural pattern recognition. Constructing base classifiers when the input patterns are graph based representations is not an easy problem. In this work, we make use of the graph embedding methodology in order to construct different feature vector representations for graphs. The graph of words embedding assigns a feature vector to every graph by counting unary and binary relations between node representatives and combining these pieces of information into a single vector. Selecting different node representatives leads to different vectorial representations and therefore to different base classifiers that can be combined. We experimentally show how this methodology significantly improves the classification of graphs with respect to single base classifiers. |
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Napoles, Italy |
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Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @GVR2011 |
Serial |
1745 |
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Permanent link to this record |
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Author |
Naila Murray; Maria Vanrell; Xavier Otazu; C. Alejandro Parraga |
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Title |
Saliency Estimation Using a Non-Parametric Low-Level Vision Model |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
433-440 |
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Keywords |
Gaussian mixture model;ad hoc parameter selection;center-surround inhibition windows;center-surround mechanism;color appearance model;convolution;eye-fixation data;human vision;innate spatial pooling mechanism;inverse wavelet transform;low-level visual front-end;nonparametric low-level vision model;saliency estimation;saliency map;scale integration;scale-weighted center-surround response;scale-weighting function;visual task;Gaussian processes;biology;biology computing;colour vision;computer vision;visual perception;wavelet transforms |
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Abstract |
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to construct a saliency map. However, integrating spatial information and justifying the choice of various parameter values remain open problems. In this paper we show that an efficient model of color appearance in human vision, which contains a principled selection of parameters as well as an innate spatial pooling mechanism, can be generalized to obtain a saliency model that outperforms state-of-the-art models. Scale integration is achieved by an inverse wavelet transform over the set of scale-weighted center-surround responses. The scale-weighting function (termed ECSF) has been optimized to better replicate psychophysical data on color appearance, and the appropriate sizes of the center-surround inhibition windows have been determined by training a Gaussian Mixture Model on eye-fixation data, thus avoiding ad-hoc parameter selection. Additionally, we conclude that the extension of a color appearance model to saliency estimation adds to the evidence for a common low-level visual front-end for different visual tasks. |
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Address |
Colorado Springs |
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Edition |
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ISSN |
1063-6919 |
ISBN |
978-1-4577-0394-2 |
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Expedition |
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Conference |
CVPR |
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Notes |
CIC |
Approved |
no |
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Call Number |
Admin @ si @ MVO2011 |
Serial |
1757 |
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Permanent link to this record |
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Author |
Nataliya Shapovalova; Wenjuan Gong; Marco Pedersoli; Xavier Roca; Jordi Gonzalez |
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Title |
On Importance of Interactions and Context in Human Action Recognition |
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 |
58-66 |
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Keywords |
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Abstract |
This paper is focused on the automatic recognition of human events in static images. Popular techniques use knowledge of the human pose for inferring the action, and the most recent approaches tend to combine pose information with either knowledge of the scene or of the objects with which the human interacts. Our approach makes a step forward in this direction by combining the human pose with the scene in which the human is placed, together with the spatial relationships between humans and objects. Based on standard, simple descriptors like HOG and SIFT, recognition performance is enhanced when these three types of knowledge are taken into account. Results obtained in the PASCAL 2010 Action Recognition Dataset demonstrate that our technique reaches state-of-the-art results using simple descriptors and classifiers. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
J. Vitria, J.M. Sanches, and M. Hernandez |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
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Area |
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Expedition |
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Conference |
IbPRIA |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ SGP2011 |
Serial |
1750 |
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Permanent link to this record |
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Author |
Carlo Gatta; Simone Balocco; Victoria Martin Yuste; Ruben Leta; Petia Radeva |
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Title |
Non-rigid Multi-modal Registration of Coronary Arteries Using SIFTflow |
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 |
159-166 |
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Keywords |
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Abstract |
The fusion of clinically relevant information coming from different image modalities is an important topic in medical imaging. In particular, different cardiac imaging modalities provides complementary information for the physician: Computer Tomography Angiography (CTA) provides reliable pre-operative information on arteries geometry, even in the presence of chronic total occlusions, while X-Ray Angiography (XRA) allows intra-operative high resolution projections of a specific artery. The non-rigid registration of arteries between these two modalities is a difficult task. In this paper we propose the use of SIFTflow, in registering CTA and XRA images. At the best of our knowledge, this paper proposed SIFTflow as a XRay-CTA registration method for the first time in the literature. To highlight the arteries, so to guide the registration process, the well known Vesselness method has been employed. Results confirm that, to the aim of registration, the arteries must be highlighted and background objects removed as much as possible. Moreover, the comparison with the well known Free Form Deformation technique, suggests that SIFTflow has a great potential in the registration of multi-modal medical images. |
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Address |
Las Palmas de Gran Canaria. Spain |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Sanches; Mario Hernandez |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ GBM2011 |
Serial |
1752 |
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Permanent link to this record |
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Author |
Xavier Perez Sala; Cecilio Angulo; Sergio Escalera |
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Title |
Biologically Inspired Turn Control in Robot Navigation |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
187-196 |
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Abstract |
An exportable and robust system for turn control using only camera images is proposed for path execution in robot navigation. Robot motion information is extracted in the form of optical flow from SURF robust descriptors of consecutive frames in the image sequence. This information is used to compute the instantaneous rotation angle. Finally, control loop is closed correcting robot displacements when it is requested for a turn command. The proposed system has been successfully tested on the four-legged Sony Aibo robot. |
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Address |
Lleida |
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ISBN |
978-1-60750-841-0 |
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Conference |
CCIA |
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Notes |
HuPBA;MILAB |
Approved |
no |
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Call Number |
Admin @ si @ PAE2011a |
Serial |
1753 |
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Permanent link to this record |
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Author |
Antonio Hernandez; Carlo Gatta; Laura Igual; Sergio Escalera; Petia Radeva |
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Title |
Automatic Angiography Segmentation Based on Improved Graph-cut |
Type |
Conference Article |
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Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Conference |
TICGI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ HGI2011 |
Serial |
1754 |
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Permanent link to this record |
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Author |
Laura Igual; Antonio Hernandez; Sergio Escalera; Miguel Reyes; Josep Moya; Joan Carles Soliva; Jordi Faquet; Oscar Vilarroya; Petia Radeva |
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Title |
Automatic Techniques for Studying Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
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Year |
2011 |
Publication |
Jornada TIC Salut Girona |
Abbreviated Journal |
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Conference |
TICGI |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ IHE2011 |
Serial |
1755 |
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Permanent link to this record |
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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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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 |
Editor |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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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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Permanent link to this record |
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Author |
Mario Rojas; David Masip; Jordi Vitria |
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Title |
Predicting Dominance Judgements Automatically: A Machine Learning Approach. |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE International Workshop on Social Behavior Analysis |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
939-944 |
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Keywords |
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Abstract |
The amount of multimodal devices that surround us is growing everyday. In this context, human interaction and communication have become a focus of attention and a hot topic of research. A crucial element in human relations is the evaluation of individuals with respect to facial traits, what is called a first impression. Studies based on appearance have suggested that personality can be expressed by appearance and the observer may use such information to form judgments. In the context of rapid facial evaluation, certain personality traits seem to have a more pronounced effect on the relations and perceptions inside groups. The perception of dominance has been shown to be an active part of social roles at different stages of life, and even play a part in mate selection. The aim of this paper is to study to what extent this information is learnable from the point of view of computer science. Specifically we intend to determine if judgments of dominance can be learned by machine learning techniques. We implement two different descriptors in order to assess this. The first is the histogram of oriented gradients (HOG), and the second is a probabilistic appearance descriptor based on the frequencies of grouped binary tests. State of the art classification rules validate the performance of both descriptors, with respect to the prediction task. Experimental results show that machine learning techniques can predict judgments of dominance rather accurately (accuracies up to 90%) and that the HOG descriptor may characterize appropriately the information necessary for such task. |
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Address |
Santa Barbara, CA |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
978-1-4244-9140-7 |
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Conference |
SBA |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ RMV2011b |
Serial |
1760 |
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Permanent link to this record |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Approximate Convex Hulls Family for One-Class Cassification |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Workshop on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
106-115 |
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Keywords |
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Abstract |
In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification. |
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Address |
Napoli, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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Language |
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Summary Language |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPR2011b |
Serial |
1761 |
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Permanent link to this record |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
User Verification From Walking Activity. First Steps Towards a Personal Verification System |
Type |
Conference Article |
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Year |
2011 |
Publication |
1st International Conference on Pervasive and Embedded Computing and Communication Systems |
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Address |
Algarve, Portugal |
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PECCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ CPR2011c |
Serial |
1762 |
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Permanent link to this record |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
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Title |
A Non-Rigid Feature Extraction Method for Shape Recognition |
Type |
Conference Article |
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Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
987-991 |
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Abstract |
This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. |
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Address |
Beijing; China; September 2011 |
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ISBN |
978-0-7695-4520-2 |
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ICDAR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ AFV2011 |
Serial |
1763 |
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Author |
Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez |
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Title |
A Coarse-to-fine Approach for fast Deformable Object Detection |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
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Pages |
1353-1360 |
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Address |
Colorado Springs; USA |
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CVPR |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ PVG2011 |
Serial |
1764 |
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Author |
Miguel Oliveira; Angel Sappa; V.Santos |
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Title |
Unsupervised Local Color Correction for Coarsely Registered Images |
Type |
Conference Article |
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Year |
2011 |
Publication |
IEEE conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
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Pages |
201-208 |
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Abstract |
The current paper proposes a new parametric local color correction technique. Initially, several color transfer functions are computed from the output of the mean shift color segmentation algorithm. Secondly, color influence maps are calculated. Finally, the contribution of every color transfer function is merged using the weights from the color influence maps. The proposed approach is compared with both global and local color correction approaches. Results show that our method outperforms the technique ranked first in a recent performance evaluation on this topic. Moreover, the proposed approach is computed in about one tenth of the time. |
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Address |
Colorado Springs |
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ISSN |
1063-6919 |
ISBN |
978-1-4577-0394-2 |
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CVPR |
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Notes |
ADAS |
Approved |
no |
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Call Number |
Admin @ si @ OSS2011; ADAS @ adas @ |
Serial |
1766 |
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Permanent link to this record |