Pedestrian Tracking in Infrared from Moving Vehicles

The automatic detection and tracking of pedestrians in imagery constitute important and challenging problems both in computer vision and driver assistance systems. We address these problems for the case of a forward looking monocular infrared camera under strong vehicle induced camera motion. An integrated detection & tracking strategy is introduced based on a state-of-the-art feature based object detector originally developed for images in the visual spectrum. The proposed pedestrian detection algorithm can be applied to both infrared and visual imagery. We show the difficulties arising from the specifics of infrared data under strong camera motion and how to tackle these problems by replacing common motion models like the Kalman filter by a feature matching approach.