Kinzel and Dickmanns 1992 : A computational framework for dynamic scene analysis with respect to 3D-real-time tracking of human motion in typical road environment is presented. In contrast to the practice of many pattern recognition techniques which refrain from considering the underlying signal process, this approach utilizes a modified observer concept from control theory to keep track of changing image features and to aggregate them in a deductive rather than an inductive manner. A procedure of recursive estimation of limb states is derived for humans modeled as mechanical multi-body system; it is supported and updated by feature based image sequence processing. For system development with versatile input signals and for an assessment of estimator performance an extensive animation tool has been designed. The proposed approach requires moderate computational power so that the complex recognition task may be accomplished in real-time in the near future. It promises less redundancy and may serve as a simulation of perception in general.