Pedestrian Detection and Tracking Based on Far Infrared Visual Information

This article discusses a pedestrian detector for an experimental vehicle, based on visual information from a single far infrared camera. The system considers three consecutive processes for each image. Once the candidates’ heads have been extracted, regions of interest are resized based on the distance to the camera and then filtered by its vertical edges symmetry. Once the bounding boxes of possible pedestrians are picked a spatial correlation with some template models takes place. Finally, detected pedestrians are tracked, contrasting their position on successive frames. The results are satisfactory, classifying correctly almost 96% of pedestrians closer than 45m to the vehicle.