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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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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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Las Palmas de Gran Canaria. Spain |
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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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ISBN |
978-3-642-21256-7 |
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IbPRIA |
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DAG |
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no |
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Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
6713 |
Issue |
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Pages |
36-45 |
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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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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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978-3-642-21556-8 |
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MCS |
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DAG |
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no |
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Call Number |
Admin @ si @GVR2011 |
Serial |
1745 |
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Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
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Title |
Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Innovations in Intelligent Image Analysis |
Abbreviated Journal ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
339 |
Issue |
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Pages |
7-29 |
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Abstract |
A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images. |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
H. Kawasnicka; L.Jain |
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ISSN |
1860-949X |
ISBN |
978-3-642-17933-4 |
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Notes |
MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ ETP2011 |
Serial |
1746 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
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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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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
6669 |
Issue |
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Pages |
58-66 |
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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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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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IbPRIA |
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Notes |
ISE |
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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 |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Subtle Facial Expression Recognition in Still Images and Videos |
Type |
Book Chapter |
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Year |
2011 |
Publication |
Advances in Face Image Analysis: Techniques and Technologies |
Abbreviated Journal ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Issue |
14 |
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259-277 |
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Abstract |
This chapter addresses the recognition of basic facial expressions. It has three main contributions. First, the authors introduce a view- and texture independent schemes that exploits facial action parameters estimated by an appearance-based 3D face tracker. they represent the learned facial actions associated with different facial expressions by time series. Two dynamic recognition schemes are proposed: (1) the first is based on conditional predictive models and on an analysis-synthesis scheme, and (2) the second is based on examples allowing straightforward use of machine learning approaches. Second, the authors propose an efficient recognition scheme based on the detection of keyframes in videos. Third, the authors compare the dynamic scheme with a static one based on analyzing individual snapshots and show that in general the former performs better than the latter. The authors then provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). |
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Publisher |
IGI-Global |
Place of Publication |
New York, USA |
Editor |
Yu-Jin Zhang |
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978-1-6152-0991-0 |
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Notes |
OR;MV |
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no |
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Call Number |
Admin @ si @ DoR2011 |
Serial |
1751 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
6669 |
Issue |
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Pages |
159-166 |
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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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Las Palmas de Gran Canaria. Spain |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Sanches; Mario Hernandez |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Pages |
187-196 |
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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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978-1-60750-841-0 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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TICGI |
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MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ HGI2011 |
Serial |
1754 |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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TICGI |
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MILAB;HuPBA |
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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 |
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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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939-944 |
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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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Santa Barbara, CA |
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978-1-4244-9140-7 |
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SBA |
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OR;MV |
Approved |
no |
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Call Number |
Admin @ si @ RMV2011b |
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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 ![sorted by Abbreviated Journal field, descending order (down)](img/sort_desc.gif) |
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Volume |
6713 |
Issue |
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106-115 |
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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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Napoli, Italy |
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Springer Berlin Heidelberg |
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Carlo Sansone; Josef Kittler; Fabio Roli |
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0302-9743 |
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978-3-642-21556-8 |
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MILAB;HuPBA |
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Admin @ si @ CPR2011b |
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1761 |
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Author |
Pierluigi Casale; Oriol Pujol; Petia Radeva |
![find record details (via OpenURL) openurl](img/xref.gif)
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User Verification From Walking Activity. First Steps Towards a Personal Verification System |
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2011 |
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1st International Conference on Pervasive and Embedded Computing and Communication Systems |
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Algarve, Portugal |
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PECCS |
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MILAB;HuPBA |
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no |
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Admin @ si @ CPR2011c |
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1762 |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
![goto web page url](img/www.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
A Non-Rigid Feature Extraction Method for Shape Recognition |
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Conference Article |
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2011 |
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11th International Conference on Document Analysis and Recognition |
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987-991 |
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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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Beijing; China; September 2011 |
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978-0-7695-4520-2 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ AFV2011 |
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1763 |
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Author |
Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A Coarse-to-fine Approach for fast Deformable Object Detection |
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Conference Article |
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2011 |
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IEEE conference on Computer Vision and Pattern Recognition |
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1353-1360 |
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Colorado Springs; USA |
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CVPR |
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ISE |
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Admin @ si @ PVG2011 |
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1764 |
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