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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.
Address Palma de Mallorca (Spain)
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Notes ADAS Approved no
Call Number ADAS @ adas @ GSL2006 Serial 672
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