| Records |
| Author |
Joan Arnedo-Moreno; Agata Lapedriza |
| Title |
Visualizing key authenticity: turning your face into your public key |
Type |
Conference Article |
| Year |
2010 |
Publication |
6th China International Conference on Information Security and Cryptology |
Abbreviated Journal |
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Volume  |
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Issue |
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Pages |
605-618 |
| Keywords |
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| Abstract |
Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process. |
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LNCS |
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Inscrypt |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ ArL2010c |
Serial |
2149 |
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| Author |
Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera |
| Title |
Deteccion automatica de la dominancia en conversaciones diadicas |
Type |
Journal Article |
| Year |
2010 |
Publication |
Escritos de Psicologia |
Abbreviated Journal |
EP |
| Volume |
3 |
Issue |
2 |
Pages |
41–45 |
| Keywords |
Dominance detection; Non-verbal communication; Visual features |
| Abstract |
Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers' opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences. |
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| ISSN |
1989-3809 |
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| Notes |
HUPBA; OR; MILAB;MV |
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no |
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BCNPCL @ bcnpcl @ EMV2010 |
Serial |
1315 |
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| Author |
O. Fors; J. Nuñez; Xavier Otazu; A. Prades; Robert D. Cardinal |
| Title |
Improving the Ability of Image Sensors to Detect Faint Stars and Moving Objects Using Image Deconvolution Techniques |
Type |
Journal Article |
| Year |
2010 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
10 |
Issue |
3 |
Pages |
1743–1752 |
| Keywords |
image processing; image deconvolution; faint stars; space debris; wavelet transform |
| Abstract |
Abstract: In this paper we show how the techniques of image deconvolution can increase the ability of image sensors as, for example, CCD imagers, to detect faint stars or faint orbital objects (small satellites and space debris). In the case of faint stars, we show that this benefit is equivalent to double the quantum efficiency of the used image sensor or to increase the effective telescope aperture by more than 30% without decreasing the astrometric precision or introducing artificial bias. In the case of orbital objects, the deconvolution technique can double the signal-to-noise ratio of the image, which helps to discover and control dangerous objects as space debris or lost satellites. The benefits obtained using CCD detectors can be extrapolated to any kind of image sensors. |
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CIC |
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no |
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CAT @ cat @ FNO2010 |
Serial |
1285 |
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| Author |
Xavier Otazu; C. Alejandro Parraga; Maria Vanrell |
| Title |
Towards a unified chromatic inducction model |
Type |
Journal Article |
| Year |
2010 |
Publication |
Journal of Vision |
Abbreviated Journal |
VSS |
| Volume |
10 |
Issue |
12:5 |
Pages |
1-24 |
| Keywords |
Visual system; Color induction; Wavelet transform |
| Abstract |
In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data. |
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CIC |
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no |
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CAT @ cat @ OPV2010 |
Serial |
1450 |
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| Author |
Albert Ali Salah; E. Pauwels; R. Tavenard; Theo Gevers |
| Title |
T-Patterns Revisited: Mining for Temporal Patterns in Sensor Data |
Type |
Journal Article |
| Year |
2010 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
| Volume |
10 |
Issue |
8 |
Pages |
7496-7513 |
| Keywords |
sensor networks; temporal pattern extraction; T-patterns; Lempel-Ziv; Gaussian mixture model; MERL motion data |
| Abstract |
The trend to use large amounts of simple sensors as opposed to a few complex sensors to monitor places and systems creates a need for temporal pattern mining algorithms to work on such data. The methods that try to discover re-usable and interpretable patterns in temporal event data have several shortcomings. We contrast several recent approaches to the problem, and extend the T-Pattern algorithm, which was previously applied for detection of sequential patterns in behavioural sciences. The temporal complexity of the T-pattern approach is prohibitive in the scenarios we consider. We remedy this with a statistical model to obtain a fast and robust algorithm to find patterns in temporal data. We test our algorithm on a recent database collected with passive infrared sensors with millions of events. |
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Conference |
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| Notes |
ALTRES;ISE |
Approved |
no |
| Call Number |
Admin @ si @ SPT2010 |
Serial |
1845 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Error-Correcting Output Codes Library |
Type |
Journal Article |
| Year |
2010 |
Publication |
Journal of Machine Learning Research |
Abbreviated Journal |
JMLR |
| Volume |
11 |
Issue |
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Pages |
661-664 |
| Keywords |
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| Abstract |
(Feb):661−664
In this paper, we present an open source Error-Correcting Output Codes (ECOC) library. The ECOC framework is a powerful tool to deal with multi-class categorization problems. This library contains both state-of-the-art coding (one-versus-one, one-versus-all, dense random, sparse random, DECOC, forest-ECOC, and ECOC-ONE) and decoding designs (hamming, euclidean, inverse hamming, laplacian, β-density, attenuated, loss-based, probabilistic kernel-based, and loss-weighted) with the parameters defined by the authors, as well as the option to include your own coding, decoding, and base classifier. |
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Edition |
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| ISSN |
1532-4435 |
ISBN |
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Medium |
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Conference |
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| Notes |
MILAB;HUPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ EPR2010c |
Serial |
1286 |
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| Author |
Antonio Lopez; Joan Serrat; Cristina Cañero; Felipe Lumbreras; T. Graf |
| Title |
Robust lane markings detection and road geometry computation |
Type |
Journal Article |
| Year |
2010 |
Publication |
International Journal of Automotive Technology |
Abbreviated Journal |
IJAT |
| Volume |
11 |
Issue |
3 |
Pages |
395–407 |
| Keywords |
lane markings |
| Abstract |
Detection of lane markings based on a camera sensor can be a low-cost solution to lane departure and curve-over-speed warnings. A number of methods and implementations have been reported in the literature. However, reliable detection is still an issue because of cast shadows, worn and occluded markings, variable ambient lighting conditions, for example. We focus on increasing detection reliability in two ways. First, we employed an image feature other than the commonly used edges: ridges, which we claim addresses this problem better. Second, we adapted RANSAC, a generic robust estimation method, to fit a parametric model of a pair of lane lines to the image features, based on both ridgeness and ridge orientation. In addition, the model was fitted for the left and right lane lines simultaneously to enforce a consistent result. Four measures of interest for driver assistance applications were directly computed from the fitted parametric model at each frame: lane width, lane curvature, and vehicle yaw angle and lateral offset with regard the lane medial axis. We qualitatively assessed our method in video sequences captured on several road types and under very different lighting conditions. We also quantitatively assessed it on synthetic but realistic video sequences for which road geometry and vehicle trajectory ground truth are known. |
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Thesis |
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| Publisher |
The Korean Society of Automotive Engineers |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1229-9138 |
ISBN |
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Medium |
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| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ LSC2010 |
Serial |
1300 |
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| Author |
Marçal Rusiñol; Josep Llados; Gemma Sanchez |
| Title |
Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings |
Type |
Journal Article |
| Year |
2010 |
Publication |
Pattern Analysis and Applications |
Abbreviated Journal |
PAA |
| Volume |
13 |
Issue |
3 |
Pages |
321-331 |
| Keywords |
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| Abstract |
In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. |
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Thesis |
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Springer-Verlag |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
1433-7541 |
ISBN |
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DAG |
Approved |
no |
| Call Number |
DAG @ dag @ RLS2010 |
Serial |
1165 |
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| Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas |
| Title |
Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model |
Type |
Journal Article |
| Year |
2010 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
13 |
Issue |
3 |
Pages |
229–241 |
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| Abstract |
One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes. |
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Springer-Verlag |
Place of Publication |
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Edition |
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| ISSN |
1433-2833 |
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| Notes |
DAG; IF 2009: 1,213 |
Approved |
no |
| Call Number |
DAG @ dag @ FLS2010a |
Serial |
1288 |
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| Author |
Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas |
| Title |
Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems |
Type |
Journal Article |
| Year |
2010 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
13 |
Issue |
3 |
Pages |
187-207 |
| Keywords |
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| Abstract |
This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results. |
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Springer-Verlag |
Place of Publication |
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1433-2833 |
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DAG |
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no |
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DAG @ dag @ DVP2010 |
Serial |
1289 |
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| Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke |
| Title |
A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores |
Type |
Journal Article |
| Year |
2010 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
13 |
Issue |
4 |
Pages |
243-259 |
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| Abstract |
The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers. |
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Springer-Verlag |
Place of Publication |
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1433-2833 |
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| Notes |
DAG; CAT;CIC |
Approved |
no |
| Call Number |
FLS2010b |
Serial |
1319 |
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| Author |
David Rotger; Petia Radeva; N. Bruining |
| Title |
Automatic Detection of Bioabsorbable Coronary Stents in IVUS Images using a Cascade of Classifiers |
Type |
Journal Article |
| Year |
2010 |
Publication |
IEEE Transactions on Information Technology in Biomedicine |
Abbreviated Journal |
TITB |
| Volume |
14 |
Issue |
2 |
Pages |
535 – 537 |
| Keywords |
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| Abstract |
Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the late restenosis. These stents made of poly-L-lactic acid cause a very subtle acoustic shadow (compared to the metallic ones) making difficult the automatic detection and measurements in images. In this paper, we propose a novel approach based on a cascade of GentleBoost classifiers to detect the stent struts using structural features to code the information of the different subregions of the struts. A stochastic gradient descent method is applied to optimize the overall performance of the detector. Validation results of struts detection are very encouraging with an average F-measure of 81%. |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ RRB2010 |
Serial |
1287 |
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| Author |
Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
| Title |
A Content Spotting System For Line Drawing Graphic Document Images |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
20 |
Issue |
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Pages |
3420–3423 |
| Keywords |
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| Abstract |
We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents. |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
Medium |
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Conference |
ICPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LBR2010b |
Serial |
1460 |
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| Author |
Dani Rowe; Jordi Gonzalez; Marco Pedersoli; Juan J. Villanueva |
| Title |
On Tracking Inside Groups |
Type |
Journal Article |
| Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
| Volume |
21 |
Issue |
2 |
Pages |
113–127 |
| Keywords |
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| Abstract |
This work develops a new architecture for multiple-target tracking in unconstrained dynamic scenes, which consists of a detection level which feeds a two-stage tracking system. A remarkable characteristic of the system is its ability to track several targets while they group and split, without using 3D information. Thus, special attention is given to the feature-selection and appearance-computation modules, and to those modules involved in tracking through groups. The system aims to work as a stand-alone application in complex and dynamic scenarios. No a-priori knowledge about either the scene or the targets, based on a previous training period, is used. Hence, the scenario is completely unknown beforehand. Successful tracking has been demonstrated in well-known databases of both indoor and outdoor scenarios. Accurate and robust localisations have been yielded during long-term target merging and occlusions. |
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Thesis |
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Springer-Verlag |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Title |
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Edition |
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| ISSN |
0932-8092 |
ISBN |
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| Notes |
ISE |
Approved |
no |
| Call Number |
ISE @ ise @ RGP2010 |
Serial |
1158 |
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| Author |
Sergio Escalera; Oriol Pujol; Petia Radeva |
| Title |
Traffic sign recognition system with β -correction |
Type |
Journal Article |
| Year |
2010 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
| Volume |
21 |
Issue |
2 |
Pages |
99–111 |
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| Abstract |
Traffic sign classification represents a classical application of multi-object recognition processing in uncontrolled adverse environments. Lack of visibility, illumination changes, and partial occlusions are just a few problems. In this paper, we introduce a novel system for multi-class classification of traffic signs based on error correcting output codes (ECOC). ECOC is based on an ensemble of binary classifiers that are trained on bi-partition of classes. We classify a wide set of traffic signs types using robust error correcting codings. Moreover, we introduce the novel β-correction decoding strategy that outperforms the state-of-the-art decoding techniques, classifying a high number of classes with great success. |
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Springer-Verlag |
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0932-8092 |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ EPR2010a |
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1276 |
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