TY  - STD
AU  - David Geronimo
AU  - Angel Sappa
AU  - Antonio Lopez
AU  - Daniel Ponsa
PY  - 2006//
TI  - Pedestrian Detection Using AdaBoost Learning of Features and Vehicle Pitch Estimation
KW  - ADAS
KW  - pedestrian detection
KW  - adaboost learning
KW  - pitch estimation
KW  - haar wavelets
KW  - edge orientation histograms.
N2  - 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.
UR  - http://www.cvc.uab.es/adas/publications/geronimo_viip2006.pdf
L1  - http://refbase.cvc.uab.es/files/GSL2006.pdf
N1  - ADAS
ID  - David Geronimo2006
ER  -