Using adaptive threshold to detect pedestrians crossing on a street for Advanced Driver Assistance Systems
Jorge Martínez‐Carballido, Moises Morales-Velazquez · 2012
Advanced Driver Assistance Systems (ADAS) are becoming of major relevance for driver assistance. Pedestrian Protection Systems are part of ADAS. It is well known that driver distraction on his/her driving is a major cause of traffic accidents, and giving the environment variability while driving it is a challenging area of research. This work shows that by reducing the search space to critical areas, not requiring background elimination, not ROI detection and selection, and as a result simplifying the algorithm for pedestrian detection giving a good approach. The algorithm parameterizes image resolution, thus allowing for different camera resolutions that surely will continue to improve. This work uses at its core the fact that a pedestrian has at least a shoe in contact with the pavement, together with the alarm zones to assist the driver is enough information for an ADAS to decide on actions for driver assistance. On a test set of 46 test images that were taken on a real urban environment this work has results that show an 89% correct detection on a real outdoor environment.