Reinforcing the reliability of pedestrian detection in far-infrared sensing

In this contribution we describe a method to improve the reliability of monocular far-infrared pedestrian detection. In contrast to many other solutions using heuristic approaches, we use a statistical approach, i.e., a pixel classification for head detection in comparison with a classifier for body detection to investigate the performance of pedestrian detection. Using a head detector leads to a significant improvement in the detection precision and promises further advantages in combination with a body detector.