Survey of Pedestrian Detection for Advanced Driver Assistance Systems
D. Geronimo and A. M. Lopez and A. D. Sappa and T. Graf

@ARTICLE{5010438,
author={D. Geronimo and A. M. Lopez and A. D. Sappa and T. Graf},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Survey of Pedestrian Detection for Advanced Driver Assistance Systems},
year={2010},
volume={32},
number={7},
pages={1239-1258},
abstract={Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one--after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges.},
keywords={driver information systems;advanced driver assistance systems;pedestrian detection;pedestrian protection systems;traffic safety;ADAS;on-board vision;pedestrian detection;survey.;Accident Prevention;Accidents, Traffic;Automobile Driving;Humans;Image Processing, Computer-Assisted;Pattern Recognition, Automated;Walking},
doi={10.1109/TPAMI.2009.122},
ISSN={0162-8828},
month={July},}