This paper is concerned with the problem of analysing articulated motion in image sequences, especially applied to case of the human motion. We have developed an approach to track the contours of a moving articulated structure, designed in a purely 2D+t form avoiding explicit and dedicated models. This method exploits spatio-temporal XT-slices of the image sequence volume XYT, where articulated motion, such as the gait of a walker, turns out to reveal typical trajectory providing relevant "signatures". We propose a reconstruction algorithm of these significant trajectories, operating on-line and resorting to an original predictive model in order to deal with occultation periods. This paradigm provides the basis of trajectory classification and recognition schemes. Results are presented for real-world images depicting human movement of gestures and walking.