The domain of image sequence analysis in order to get trajectories is widely expanding and, usually, the designed systems match well the application itself. Indeed, according to the constraints taken from the application, more or less information can be extracted and that makes the algorithms more or less complicated. However, all of them depend on the study of temporal events and the trajectory extraction process is led by the introduction of constraints and hypotheses about the objects and then by checking they are good. The proposed paper presents a technique that can fit most of the applications by adapting the spatio-temporal association criteria and shows how it is applied to human motion analysis. After human motion analysis has been presented in the introduction, its problems are listed in part one. In part two, the tracking targets, used to materialize the pertinent parts of the body (to make their extraction easy), and the image sequence analysis system, are described. The automatic target tracking algorithm is presented in the third part. It allows the user to reduce significantly the number of operator interventions during the tracking process. Lastly, we show that the 3D tracking is practically implicit when the 2D tracking is made. In part four, results of 2D and 3D tracking are given. The solving of the target loss problem is also described with examples. This paper ends with some perspectives that can improve our tracking algorithm.