In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance
cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate
infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of
detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance
cue helps to locate the exact position of pedestrians.