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Author |
Marçal Rusiñol |
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Title |
A Model of Vectorial Signatures in Terms of Expressive Sub-Shapes: Symbol Indexation in Technical Documents |
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Report |
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2006 |
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CVC Technical Report #94 |
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CVC (UAB) |
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DAG @ dag @ Rus2006 |
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668 |
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Author |
Jose Antonio Rodriguez |
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Title |
Pen-based Interfaces and Recognition: Application to Proofreading Interpretation |
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2006 |
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CVC Technical Report #96 |
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Admin @ si @ Rod2006 |
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669 |
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Author |
Miquel Ferrer |
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Title |
Spectral Median Graphs and its Application to Graphical Symbol Recognition |
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2006 |
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CVC Technical Report #95 |
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Admin @ si @ Fer2006 |
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670 |
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Author |
Angel Sappa; David Geronimo; Fadi Dornaika; Antonio Lopez |
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Title |
Real Time Vehicle Pose Using On-Board Stereo Vision System |
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Year |
2006 |
Publication |
International Conference on Image Analysis and Recognition |
Abbreviated Journal |
ICIAR |
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LNCS 4142 |
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205–216 |
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This paper presents a robust technique for a real time estimation of both camera’s position and orientation—referred as pose. A commercial stereo vision system is used. Unlike previous approaches, it can be used either for urban or highway scenarios. The proposed technique consists of two stages. Initially, a compact 2D representation of the original 3D data points is computed. Then, a RANSAC based least squares approach is used for fitting a plane to the road. At the same time,
relative camera’s position and orientation are computed. The proposed technique is intended to be used on a driving assistance scheme for applications such as obstacle or pedestrian detection. Experimental results on urban environments with different road geometries are presented. |
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ADAS |
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ADAS @ adas @ SGD2006b |
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671 |
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Author |
David Geronimo; Angel Sappa; Antonio Lopez; Daniel Ponsa |
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Title |
Pedestrian Detection Using AdaBoost Learning of Features and Vehicle Pitch Estimation |
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Miscellaneous |
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Year |
2006 |
Publication |
6th IASTED International Conference on Visualization, Imaging and Image Processing |
Abbreviated Journal |
VIIP |
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400–405 |
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ADAS, pedestrian detection, adaboost learning, pitch estimation, haar wavelets, edge orientation histograms. |
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In this paper we propose a combination of different Haar filter sets and Edge Orientation Histograms (EOH) in order to learn a model for pedestrian detection. As we will show, with the addition of EOH we obtain better ROCs than using Haar filters alone. Hence, a model consisting of discriminant features, selected by AdaBoost, is applied at pedestrian-sized image windows in order to perform
the classification. Additionally, taking into account the final application, a driver assistance system with realtime requirements, we propose a novel stereo-based camera pitch estimation to reduce the number of explored windows.
With this approach, the system can work in urban roads, as will be illustrated by current results. |
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Palma de Mallorca (Spain) |
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ADAS |
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ADAS @ adas @ GSL2006 |
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672 |
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Author |
V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich |
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Title |
Adaptive Correlation Filters for Pattern Recognition |
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Journal |
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2006 |
Publication |
Pattern Recognition and Image Analysis |
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16 |
Issue |
3 |
Pages |
425-431 |
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Pattern recognition, Correlation filters, A adaptive filters |
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Adaptive correlation filters based on synthetic discriminant functions (SDFs) for reliable pattern recognition are proposed. A given value of discrimination capability can be achieved by adapting a SDF filter to the input scene. This can be done by iterative training. Computer simulation results obtained with the proposed filters are compared with those of various correlation filters in terms of recognition performance. |
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ISE |
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ISE @ ise @ KMA2006a |
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673 |
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Author |
V. Kober; Mikhail Mozerov; J. Alvarez-Borrego; I.A. Ovseyevich |
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Title |
Pattern Recognition of Fragmented Objects with Adaptive Correlation Filters |
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Miscellaneous |
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2006 |
Publication |
Topical Meeting on Optoinformatics / Information Photonics, 150–151 |
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Saint-Petersburg (Russia) |
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ISE @ ise @ KMA2006b |
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674 |
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Author |
Mikhail Mozerov; V. Kober; I.A. Ovseyevich |
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Title |
A Stereo Matching Algorithm with Global Smoothness Criterion |
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Miscellaneous |
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2006 |
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Topical Meeting on Optoinformatics / Information Photonics, 133–135 |
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Saint-Petersburg (Russia) |
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ISE @ ise @ MKO2006 |
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675 |
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Author |
Mikhail Mozerov; V. Kober |
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Title |
Impulse Noise Removal with Gradient Adaptive Neighborhoods |
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2006 |
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Optical Engineering, 45: 67003 |
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ISE @ ise @ MoK2006 |
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676 |
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Author |
Mikhail Mozerov |
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Title |
An Effective Stereo Matching Algorithm with Optimal Path Cost Aggregation |
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2006 |
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28th Annual Symposium of the German Association for Pattern Recognition, LNCS 4174: 617–626 |
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ISE @ ise @ Moz2006 |
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Author |
Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez |
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3D Human Motion Sequences Synchronization Using Dense Matching Algorithm |
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2006 |
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28th Annual Symposium of the German Association for Pattern Recognition, LNCS 4174: 485–494, ISBN 978–3–540–44412–1 |
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ISE @ ise @ MRR2006 |
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678 |
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Author |
E. Pastor; A. Agueda; Juan Andrade; M. Muñoz; Y. Perez; E. Planas |
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Computing the rate of spread of linear flame fronts by thermal image processing |
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2006 |
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Fire Safety Journal, 41(8):569–579 |
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Admin @ si @ PAA2006 |
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679 |
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Author |
T. Alejandra Vidal; A. Sanfeliu; Juan Andrade |
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Title |
Autonomous Single Camera Exploration |
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2006 |
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Jornada de Recerca en Automatica, Visio i Robotica |
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Barcelona (Spain) |
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Admin @ si @ VSA2006c |
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680 |
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Author |
Eduard Vazquez; Francesc Tous; Ramon Baldrich; Maria Vanrell |
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Title |
n-Dimensional Distribution Reduction Preserving its Structure |
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2006 |
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Artificial Intelligence Research and Development, M. Polit et al. (Eds.), 146: 167–175 |
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CIC |
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CAT @ cat @ VTB2006a |
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681 |
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Author |
Anton Cervantes; Gemma Sanchez; Josep Llados; Agnes Borras; Ana Rodriguez |
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Title |
Biometric Recognition Based on Line Shape Descriptors |
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2006 |
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Lecture Notes in Computer Science |
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3926 |
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346–357, |
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Abstract. In this paper we propose biometric descriptors inspired by shape signatures traditionally used in graphics recognition approaches. In particular several methods based on line shape descriptors used to iden- tify newborns from the biometric information of the ears are developed. The process steps are the following: image acquisition, ear segmentation, ear normalization, feature extraction and identification. Several shape signatures are defined from contour images. These are formulated in terms of zoning and contour crossings descriptors. Experimental results are presented to demonstrate the effectiveness of the used techniques. |
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DAG |
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DAG @ dag @ CSL2006 |
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