PT Unknown
AU David Geronimo
   Angel Sappa
   Antonio Lopez
   Daniel Ponsa
TI Pedestrian Detection Using AdaBoost Learning of Features and Vehicle Pitch Estimation
PY 2006
DE ADAS; pedestrian detection; adaboost learning; pitch estimation; haar wavelets; edge orientation histograms.
AB 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 performthe 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.
ER