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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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2006 |
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6th IASTED International Conference on Visualization, Imaging and Image Processing |
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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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David Geronimo; Antonio Lopez |
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Title |
Deteccion de Peatones para Sistemas Avanzados de Asistencia al Conductor |
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2010 |
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UAB Divulga |
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Los sistemas de asistencia al conductor, y particularmente los sistemas de protección de peatones, representan uno de los campos de investigación más activos dedicados a la mejora de la seguridad vial. El mayor desafío es el desarrollo de sistemas a bordo fiables de detección de peatones. En esta revisión del estado de la técnica de la detección de peatones, se divide el problema en diferentes etapas, cada una con responsabilidades propias dentro del sistema. Esta división facilita el posterior análisis y discusión de cada uno de los métodos en la literatura, favoreciendo la comparación entre ellos. Finalmente se discuten los temas más importantes de este campo poniendo especial énfasis en las necesidades actuales y los desafíos futuros. |
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Bellaterra (Catalonia), Spain |
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spreading;ADAS |
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ADAS @ adas @ GeL2010a |
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1414 |
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David Geronimo; Antonio Lopez |
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Title |
Sistema de deteccion de peatones |
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2010 |
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UAB Divulga |
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Durante la próxima década, los sistemas de protección de peatones jugarán un papel fundamental en el reto de mejorar la seguridad viaria. El objetivo principal de estos sistemas, detectar peatones en entornos urbanos, implica procesar imágenes de escenas exteriores desde una plataforma móvil para buscar objetos de aspecto variable como son las personas. Dadas estas dificultades, estos sistemas hacen uso de las últimas técnicas de visión por computador. Esta propuesta consiste en un sistema de tres módulos basado tanto en información 2D como en 3D. El primer módulo utiliza información 3D para hacer una estimación de los parámetros de la carretera y seleccionar regiones de interés que serán analizadas después. El segundo módulo utiliza un clasificador de ventanas 2D para etiquetar las mencionadas regiones como peatón o no peatón. El módulo final vuelve a utilizar de nuevo la información 3D para verificar las regiones clasificadas y, con información 2D, refinar los resultados finales. Los resultados experimentales son positivos tanto en rendimiento como en tiempo de cómputo. |
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Bellaterra (Spain) |
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spreading;ADAS |
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ADAS @ adas @ GeL2010b |
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1473 |
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David Guillamet; B. Moghaddam |
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Title |
Joint Distribution of Local Image Features for Appearance Moldeling. |
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2002 |
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Proceedings of the IAPR Workshop on Machine Vision Applications MVA 2002. |
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Admin @ si @ GuM2002 |
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293 |
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David Guillamet; B. Moghaddam; Jordi Vitria |
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Title |
Higher-Order Dependencies in Local Appearance Models |
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2003 |
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IEEE International Conference on Image Processing (ICIP) |
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BCNPCL @ bcnpcl @ GMV2003b |
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377 |
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David Guillamet; B. Moghaddam; Jordi Vitria |
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Title |
Modeling High-Order Dependencies in Local Appearance Models |
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2003 |
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In Pattern Recognition and Image Analysis, Lecture Notes in Computer Science. 2652: 308–316 |
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BCNPCL @ bcnpcl @ GMV2003a |
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376 |
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David Guillamet; B. Shiele; Jordi Vitria |
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Analyzing Non-negative Matrix Factorization for Image Classification. |
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2002 |
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International Conference on Pattern Recognition ICPR 2002, 2: 116–119. |
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Quebec, Canada |
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BCNPCL @ bcnpcl @ GSV2002 |
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292 |
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David Guillamet; Jordi Vitria |
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Non-negative Matrix Factorization for Face Recognition. |
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2002 |
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BCNPCL @ bcnpcl @ GuV2002a |
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280 |
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David Guillamet; Jordi Vitria |
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Classifying Faces with Non-negative Matrix Factorization. |
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2002 |
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David Guillamet; Jordi Vitria |
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Determining a Suitable Metric when using Non-negative Matrix Factorization. |
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2002 |
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IEEE International Conference on Pattern Recognition, 2: 128–131. |
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David Guillamet; Jordi Vitria |
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Non-negative Matrix Factorization to Extract Part-Based Representations. |
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2001 |
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David Guillamet; Jordi Vitria |
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Discriminant Basis for Object Classification. |
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2001 |
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11th International Conference on Image Analysis and Processing, ICIAP 2001, 256–261 |
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BCNPCL @ bcnpcl @ GuV2001c |
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103 |
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David Guillamet; Jordi Vitria |
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Non-negative Matrix Factorization to Extract Part-Based Representations. |
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2001 |
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Accepted for 4th Catalan Conference for Artificial Intelligence. |
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David Guillamet; Jordi Vitria |
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Unsupervised Learning of Part-Based Representations |
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2001 |
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Proceedings 9th International Conference CAIP 2001,700–708, W. Skarbek (Ed.): Computer Analysis of Images and Patterns, LNCS 2059, Springer Verlag, 123–134. |
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David Guillamet; Jordi Vitria |
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Unsupervised Learning of Structural Object Representations |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 2:73–78 |
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