The present paper describes some major steps in our experiment of a two-frame based approach analysis. Its application deals with 3-D time-varing scene analysis. The entire analysis process can be divided into several major steps. Here, we are concerned with four main steps: preprocessing, knowledge representation, features matching and motion estimation. The work is directly related to the problem encountered by researchers in machine intelligence area where a vision system is indispensable. For each step, experimental results are given to illustrate the performance of the algorithms of processing. Furthermore, the implemented algorithms provide somewhat versatility and flexibility in the sense that they can be applied to other tasks of scene analysis, such as: stereo vision, object recognition and dynamic scene segmentation since the problem in determining the movement of an object using successive images is similar in many ways to the problem met in optic flow analysis and stereopsis. Finally, it should be pointed out that a vision system can be easily built when combining all of these available algorithms.