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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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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 |
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Editor |
J. Vitria, J.M. Sanches, and M. Hernandez |
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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 |
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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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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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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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 |
MILAB |
Approved |
no |
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Call Number |
Admin @ si @ GBM2011 |
Serial |
1752 |
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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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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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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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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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Expedition |
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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 |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
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 |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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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 |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011a |
Serial |
1771 |
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Permanent link to this record |
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Author |
Carlo Gatta; Eloi Puertas; Oriol Pujol |
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Title |
Multi-Scale Stacked Sequential Learning |
Type |
Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
44 |
Issue |
10-11 |
Pages |
2414-2416 |
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Keywords |
Stacked sequential learning; Multiscale; Multiresolution; Contextual classification |
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Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
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Elsevier |
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LNCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ GPP2011 |
Serial |
1802 |
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Permanent link to this record |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
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Title |
Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings |
Type |
Conference Article |
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Year |
2011 |
Publication |
In proceedings of 9th IAPR Workshop on Graphic Recognition |
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Abstract |
Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words. |
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Address |
Seoul, Korea |
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Publisher |
Springer Berlin Heidelberg |
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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 |
978-3-642-36823-3 |
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Conference |
GREC |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ DLP2011c |
Serial |
1825 |
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Permanent link to this record |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
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 |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag 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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Series Editor |
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Abbreviated Series Title |
LNCS |
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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; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011b |
Serial |
1887 |
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Permanent link to this record |
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Author |
Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras |
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Title |
A massively parallel computational electrophysiology model of the heart |
Type |
Journal Article |
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Year |
2011 |
Publication |
International Journal for Numerical Methods in Biomedical Engineering |
Abbreviated Journal |
IJNMBE |
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Volume |
27 |
Issue |
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Pages |
1911-1929 |
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Keywords |
computational electrophysiology; parallelization; finite element methods |
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Abstract |
This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale. |
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Address |
Swansea (UK) |
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Corporate Author |
John Wiley & Sons, Ltd. |
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Publisher |
John Wiley & Sons, Ltd. |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ VAH2011 |
Serial |
1198 |
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Permanent link to this record |
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Author |
Daniel Ponsa; Joan Serrat; Antonio Lopez |
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Title |
On-board image-based vehicle detection and tracking |
Type |
Journal Article |
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Year |
2011 |
Publication |
Transactions of the Institute of Measurement and Control |
Abbreviated Journal |
TIM |
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Volume |
33 |
Issue |
7 |
Pages |
783-805 |
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Keywords |
vehicle detection |
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Abstract |
In this paper we present a computer vision system for daytime vehicle detection and localization, an essential step in the development of several types of advanced driver assistance systems. It has a reduced processing time and high accuracy thanks to the combination of vehicle detection with lane-markings estimation and temporal tracking of both vehicles and lane markings. Concerning vehicle detection, our main contribution is a frame scanning process that inspects images according to the geometry of image formation, and with an Adaboost-based detector that is robust to the variability in the different vehicle types (car, van, truck) and lighting conditions. In addition, we propose a new method to estimate the most likely three-dimensional locations of vehicles on the road ahead. With regards to the lane-markings estimation component, we have two main contributions. First, we employ a different image feature to the other commonly used edges: we use ridges, which are better suited to this problem. Second, we adapt RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane markings to the image features. We qualitatively assess our vehicle detection system in sequences captured on several road types and under very different lighting conditions. The processed videos are available on a web page associated with this paper. A quantitative evaluation of the system has shown quite accurate results (a low number of false positives and negatives) at a reasonable computation time. |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ PSL2011 |
Serial |
1413 |
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Permanent link to this record |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Road Detection Based on Illuminant Invariance |
Type |
Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
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Volume |
12 |
Issue |
1 |
Pages |
184-193 |
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Keywords |
road detection |
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Abstract |
By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. |
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ADAS |
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no |
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Call Number |
ADAS @ adas @ AlL2011 |
Serial |
1456 |
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Permanent link to this record |
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Author |
Muhammad Anwer Rao; David Vazquez; Antonio Lopez |
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Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
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Volume |
6855 |
Issue |
II |
Pages |
463-470 |
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Keywords |
Pedestrian Detection; Color |
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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. |
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Seville, Spain |
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Publisher |
Springer |
Place of Publication |
Berlin Heidelberg |
Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
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Language |
English |
Summary Language |
english |
Original Title |
Color Contribution to Part-Based Person Detection in Different Types of Scenarios |
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0302-9743 |
ISBN |
978-3-642-23677-8 |
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CAIP |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ RVL2011b |
Serial |
1665 |
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Permanent link to this record |
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Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-preserving smoothing of biomedical images |
Type |
Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
44 |
Issue |
9 |
Pages |
1842-1851 |
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Keywords |
Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography |
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Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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0031-3203 |
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IAM; ADAS |
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IAM @ iam @ GHB2011 |
Serial |
1526 |
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Permanent link to this record |
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Author |
Aura Hernandez-Sabate; Debora Gil; Jaume Garcia; Enric Marti |
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Title |
Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences |
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Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control |
Abbreviated Journal |
T-UFFC |
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58 |
Issue |
1 |
Pages |
60-72 |
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Keywords |
3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging |
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Abstract |
Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals. |
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0885-3010 |
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IAM;ADAS |
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no |
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IAM @ iam @ HGG2011 |
Serial |
1546 |
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Author |
Enric Marti; Ferran Poveda; Antoni Gurgui; Debora Gil |
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Title |
Aprendizaje Basado en Proyectos en Ingeniería Informática. Resultados y reflexiones de seis años de experiencia |
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Miscellaneous |
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2011 |
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Actas del Simposio-Taller JENUI 2011 |
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1-8 |
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In this workshop a 6 years experience in Project Based Learning (PBL) in Computer Graphics, Computer Engineering course at the Autonomous University of Barcelona (UAB) is presented. We use a Moodle environment suited to manage the documentation generated in PBL. The course is organized by means of two alternative routes: a classic itinerary of lectures and test-based evaluation and another with PBL. In the PBL itinerary we explain the organization in teamgroups, homework tutoring and monitoring and evaluation guidelines for students. We provide some of the work done by students, and the results of assessment surveys carried out to students during these years. We report the evolution of our PBL itinerary in terms of, both, organization and student surveys.
The workshop aims at discussing about on the advantages and disadvantages of using these active methodologies in technical degrees such as computer engineering, in order to debate about the most suitable way of organizing PBL and assessing students learning rate. |
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Sevilla, Spain |
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spanish |
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978-84-694-5440-4 |
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JENUI |
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IAM |
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no |
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Call Number |
IAM @ iam @ MPG2011 |
Serial |
1584 |
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Permanent link to this record |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
An inference model for analyzing termination conditions of Evolutionary Algorithms |
Type |
Conference Article |
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Year |
2011 |
Publication |
14th Congrès Català en Intel·ligencia Artificial |
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216-225 |
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Evolutionary Computation Convergence, Termination Conditions, Statistical Inference |
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In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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Lleida, Catalonia (Spain) |
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Associació Catalana Intel·ligència Artificial |
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978-1-60750-841-0 |
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CCIA |
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IAM |
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no |
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Call Number |
IAM @ iam @ RGG2011a |
Serial |
1677 |
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Permanent link to this record |