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Author ![]() |
David Geronimo; Angel Sappa; Antonio Lopez; Daniel Ponsa | ||||
Title | Pedestrian Detection Using AdaBoost Learning of Features and Vehicle Pitch Estimation | Type | Miscellaneous | ||
Year | 2006 | Publication | 6th IASTED International Conference on Visualization, Imaging and Image Processing | Abbreviated Journal | VIIP |
Volume | Issue | Pages | 400–405 | ||
Keywords | ADAS, pedestrian detection, adaboost learning, pitch estimation, haar wavelets, edge orientation histograms. | ||||
Abstract | 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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Address | Palma de Mallorca (Spain) | ||||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ GSL2006 | Serial | 672 | ||
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