|
Records |
Links |
|
Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
|
|
Title |
ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences |
Type |
Conference Article |
|
Year |
2009 |
Publication |
12th International Conference on Medical Image and Computer Assisted Intervention |
Abbreviated Journal |
|
|
|
Volume |
5762 |
Issue |
II |
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers. |
|
|
Address |
London, UK |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-04270-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
MICCAI |
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ CPF2009 |
Serial |
1228 |
|
Permanent link to this record |
|
|
|
|
Author |
Carlo Gatta; Oriol Pujol; Oriol Rodriguez-Leor; J. M. Ferre; Petia Radeva |
|
|
Title |
Fast Rigid Registration of Vascular Structures in IVUS Sequences |
Type |
Journal Article |
|
Year |
2009 |
Publication |
IEEE Transactions on Information Technology in Biomedicine |
Abbreviated Journal |
|
|
|
Volume |
13 |
Issue |
6 |
Pages |
106-1011 |
|
|
Keywords |
|
|
|
Abstract |
Intravascular ultrasound (IVUS) technology permits visualization of high-resolution images of internal vascular structures. IVUS is a unique image-guiding tool to display longitudinal view of the vessels, and estimate the length and size of vascular structures with the goal of accurate diagnosis. Unfortunately, due to pulsatile contraction and expansion of the heart, the captured images are affected by different motion artifacts that make visual inspection difficult. In this paper, we propose an efficient algorithm that aligns vascular structures and strongly reduces the saw-shaped oscillation, simplifying the inspection of longitudinal cuts; it reduces the motion artifacts caused by the displacement of the catheter in the short-axis plane and the catheter rotation due to vessel tortuosity. The algorithm prototype aligns 3.16 frames/s and clearly outperforms state-of-the-art methods with similar computational cost. The speed of the algorithm is crucial since it allows to inspect the corrected sequence during patient intervention. Moreover, we improved an indirect methodology for IVUS rigid registration algorithm evaluation. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1089-7771 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ GPL2009 |
Serial |
1250 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva |
|
|
Title |
Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes |
Type |
Journal Article |
|
Year |
2009 |
Publication |
Journal of Signal Processing Systems |
Abbreviated Journal |
|
|
|
Volume |
55 |
Issue |
1-3 |
Pages |
35–47 |
|
|
Keywords |
|
|
|
Abstract |
Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1939-8018 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ EPM2009 |
Serial |
1258 |
|
Permanent link to this record |
|
|
|
|
Author |
Oriol Pujol; Eloi Puertas; Carlo Gatta |
|
|
Title |
Multi-scale Stacked Sequential Learning |
Type |
Conference Article |
|
Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
|
|
|
Volume |
5519 |
Issue |
|
Pages |
262–271 |
|
|
Keywords |
|
|
|
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. |
|
|
Address |
Reykjavik, Iceland |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-02325-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
MCS |
|
|
Notes |
MILAB;HuPBA |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ PPG2009 |
Serial |
1260 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Alberto Escudero; Petia Radeva |
|
|
Title |
Circular Blurred Shape Model for Symbol Spotting in Documents |
Type |
Conference Article |
|
Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
1985-1988 |
|
|
Keywords |
|
|
|
Abstract |
Symbol spotting problem requires feature extraction strategies able to generalize from training samples and to localize the target object while discarding most part of the image. In the case of document analysis, symbol spotting techniques have to deal with a high variability of symbols' appearance. In this paper, we propose the Circular Blurred Shape Model descriptor. Feature extraction is performed capturing the spatial arrangement of significant object characteristics in a correlogram structure. Shape information from objects is shared among correlogram regions, being tolerant to the irregular deformations. Descriptors are learnt using a cascade of classifiers and Abadoost as the base classifier. Finally, symbol spotting is performed by means of a windowing strategy using the learnt cascade over plan and old musical score documents. Spotting and multi-class categorization results show better performance comparing with the state-of-the-art descriptors. |
|
|
Address |
Cairo, Egypt |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-1-4244-5653-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIP |
|
|
Notes |
MILAB;HuPBA;DAG |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ EFP2009b |
Serial |
1184 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva |
|
|
Title |
Multi-class Binary Symbol Classification with Circular Blurred Shape Models |
Type |
Conference Article |
|
Year |
2009 |
Publication |
15th International Conference on Image Analysis and Processing |
Abbreviated Journal |
|
|
|
Volume |
5716 |
Issue |
|
Pages |
1005–1014 |
|
|
Keywords |
|
|
|
Abstract |
Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements. |
|
|
Address |
Salerno, Italy |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0302-9743 |
ISBN |
978-3-642-04145-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIAP |
|
|
Notes |
MILAB;HuPBA;DAG |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ EFP2009c |
Serial |
1186 |
|
Permanent link to this record |
|
|
|
|
Author |
Mirko Arnold; Anarta Ghosh; Gerard Lacey; Stephen Patchett; Hugh Mulcahy |
|
|
Title |
Indistinct frame detection in colonoscopy videos |
Type |
Conference Article |
|
Year |
2009 |
Publication |
Machine Vision and Image Processing Conference |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
47-52 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV |
Approved |
no |
|
|
Call Number |
fernando @ fernando @ |
Serial |
2424 |
|
Permanent link to this record |
|
|
|
|
Author |
Jorge Bernal |
|
|
Title |
Use of Projection and Back-projection Methods in Bidimensional Computed Tomography Image Reconstruction |
Type |
Report |
|
Year |
2009 |
Publication |
CVC Tecnical Report |
Abbreviated Journal |
|
|
|
Volume |
141 |
Issue |
|
Pages |
|
|
|
Keywords |
Projection, Back-projection, CT scan, Euclidean geometry, Radon transform |
|
|
Abstract |
One of the biggest drawbacks related to the use of CT scanners is the cost (in memory and in time) associated. In this project many methods to simulate their functioning, but in a more feasible way (taking an industrial point of view), will be studied.
The main group of techniques that are being used are the one entitled as ’back-projection’. The concept behind is to simulate the X ray emission in CT scans by lines that cross with the image we want to reconstruct.
In the first part of this document euclidean geometry is used to face the tasks of projec- tion and back-projection. After analysing the results achieved it has been proved that this approach does not lead to a fully perfect reconstruction (and also has some other problems related to running time and memory cost). Because of this in the second part of the document ’Filtered Back-projection’ method is introduced in order to improve the results.
Filtered Back-projection methods rely on mathematical transforms (Fourier, Radon) in order to provide more accurate results that can be obtained in much less time. The main cause of this better results is the use of a filtering process before the back-projection in order to avoid high frequency-caused errors.
As a result of this project two different implementations (one for each approach) had been implemented in order to compare their performance. |
|
|
Address |
|
|
|
Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
|
|
Publisher |
|
Place of Publication |
Barcelona, Spain |
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ Ber2009 |
Serial |
1693 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
|
|
Title |
Device, system and method for measurement and analysis of contractile activity |
Type |
Patent |
|
Year |
2009 |
Publication |
US 2009/0202117 A1 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data. |
|
|
Address |
Pearl Cohen Zedek Latzer |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VSR2009 |
Serial |
1704 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Vilariño; Stephan Ameling; Gerard Lacey; Stephen Patchett; Hugh Mulcahy |
|
|
Title |
Eye Tracking Search Patterns in Expert and Trainee Colonoscopists: A Novel Method of Assessing Endoscopic Competency? |
Type |
Journal Article |
|
Year |
2009 |
Publication |
Gastrointestinal Endoscopy |
Abbreviated Journal |
GI |
|
|
Volume |
69 |
Issue |
5 |
Pages |
370 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
fernando @ fernando @ |
Serial |
2420 |
|
Permanent link to this record |
|
|
|
|
Author |
Stefan Ameling; Stephan Wirth; Dietrich Paulus; Gerard Lacey; Fernando Vilariño |
|
|
Title |
Texture-based Polyp Detection in Colonoscopy |
Type |
Conference Article |
|
Year |
2009 |
Publication |
Proc. BILDVERARBEITUNG FÜR DIE MEDIZIN |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
fernando @ fernando @ |
Serial |
2428 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Vilariño; Gerard Lacey |
|
|
Title |
QUALITY ASSESSMENT IN COLONOSCOPY New challenges through computer vision-based systems |
Type |
Conference Article |
|
Year |
2009 |
Publication |
in Proc. 3rd International Conference on Biomedical Electronics and Devices |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
800 |
Expedition |
|
Conference |
|
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
fernando @ fernando @ |
Serial |
2430 |
|
Permanent link to this record |
|
|
|
|
Author |
Oriol Pujol; David Masip |
|
|
Title |
Geometry-Based Ensembles: Toward a Structural Characterization of the Classification Boundary |
Type |
Journal Article |
|
Year |
2009 |
Publication |
IEEE Transactions on Pattern Analysis and Machine Intelligence |
Abbreviated Journal |
TPAMI |
|
|
Volume |
31 |
Issue |
6 |
Pages |
1140–1146 |
|
|
Keywords |
|
|
|
Abstract |
This article introduces a novel binary discriminative learning technique based on the approximation of the non-linear decision boundary by a piece-wise linear smooth additive model. The decision border is geometrically defined by means of the characterizing boundary points – points that belong to the optimal boundary under a certain notion of robustness. Based on these points, a set of locally robust linear classifiers is defined and assembled by means of a Tikhonov regularized optimization procedure in an additive model to create a final lambda-smooth decision rule. As a result, a very simple and robust classifier with a strong geometrical meaning and non-linear behavior is obtained. The simplicity of the method allows its extension to cope with some of nowadays machine learning challenges, such as online learning, large scale learning or parallelization, with linear computational complexity. We validate our approach on the UCI database. Finally, we apply our technique in online and large scale scenarios, and in six real life computer vision and pattern recognition problems: gender recognition, intravascular ultrasound tissue classification, speed traffic sign detection, Chagas' disease severity detection, clef classification and action recognition using a 3D accelerometer data. The results are promising and this paper opens a line of research that deserves further attention |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;HuPBA;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ PuM2009 |
Serial |
1252 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Baro |
|
|
Title |
Probabilistic Darwin Machines: A New Approach to Develop Evolutionary Object Detection |
Type |
Book Whole |
|
Year |
2009 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
Ever since computers were invented, we have wondered whether they might perform some of the human quotidian tasks. One of the most studied and still nowadays less understood problem is the capacity to learn from our experiences and how we generalize the knowledge that we acquire. One of that unaware tasks for the persons and that more interest is awakening in different scientific areas since the beginning, is the one that is known as pattern recognition. The creation of models that represent the world that surrounds us, help us for recognizing objects in our environment, to predict situations, to identify behaviors... All this information allows us to adapt ourselves and to interact with our environment. The capacity of adaptation of individuals to their environment has been related to the amount of patterns that are capable of identifying.
This thesis faces the pattern recognition problem from a Computer Vision point of view, taking one of the most paradigmatic and extended approaches to object detection as starting point. After studying this approach, two weak points are identified: The first makes reference to the description of the objects, and the second is a limitation of the learning algorithm, which hampers the utilization of best descriptors.
In order to address the learning limitations, we introduce evolutionary computation techniques to the classical object detection approach.
After testing the classical evolutionary approaches, such as genetic algorithms, we develop a new learning algorithm based on Probabilistic Darwin Machines, which better adapts to the learning problem. Once the learning limitation is avoided, we introduce a new feature set, which maintains the benefits of the classical feature set, adding the ability to describe non localities. This combination of evolutionary learning algorithm and features is tested on different public data sets, outperforming the results obtained by the classical approach. |
|
|
Address |
Barcelona (Spain) |
|
|
Corporate Author |
|
Thesis |
Ph.D. thesis |
|
|
Publisher |
Ediciones Graficas Rey |
Place of Publication |
|
Editor |
Jordi Vitria |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;HuPBA;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ Bar2009 |
Serial |
1262 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva |
|
|
Title |
Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification |
Type |
Journal Article |
|
Year |
2009 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
|
|
Volume |
10 |
Issue |
1 |
Pages |
113–126 |
|
|
Keywords |
|
|
|
Abstract |
The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1524-9050 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
OR;MILAB;HuPBA;MV |
Approved |
no |
|
|
Call Number |
BCNPCL @ bcnpcl @ BEV2008 |
Serial |
1116 |
|
Permanent link to this record |