Pedestrian Detection in Far Infrared Images based on the use of Probabilistic Templates

This article presents a validator stage for a pedestrian detection system based on the use of probabilistic models for the infrared domain. Four different models are employed in order to recognize the pose of the pedestrians; open, almost open, almost closed and fully closed legs are detected. In an attempt to overcome the drawbacks of template-matching in far infrared images, two different approaches are proposed. The algorithm has been tested on an experimental vehicle in different situations and a receiver operating characteristic has been computed.