Probabilistic template based pedestrian detection in infrared videos

In this paper we present a real time pedestrian detection system that works on low quality infrared videos. We introduce probabilistic templates to capture the variations in human shape, especially for the case where contrast is low and body parts are missing. We present experimental results on infrared videos taken from a moving vehicle in various urban street scenarios to demonstrate the feasibility of the approach.