Pedestrian Detection using Adaboost Learning of Features and Vehicle Pitch Estimation

D. Gerónimo, A.D. Sappa, A. López, and D. Ponsa (Spain)


ADAS, pedestrian detection, adaboost learning, pitch esti mation, haar wavelets, edge orientation histograms.


In this paper we propose a combination of different Haar filter sets and Edge Orientation Histograms (EOH) in or der 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 consist ing of discriminant features, selected by AdaBoost, is ap plied at pedestrian-sized image windows in order to per form the classification. Additionally, taking into account the final application, a driver assistance system with real time requirements, we propose a novel stereo-based cam era pitch estimation to reduce the number of explored win dows. With this approach, the system can work in urban roads, as will be illustrated by current results.

Important Links:

Go Back