This paper addresses the problem of recognizing articulated and deformable objects. In particular we are interested in human arm and leg articulations. Our approach is a Bayesian-Information integration of shape similarity and snakes, and naturally combines top-down & bottom-up algorithms. The bottom-up method extracts edges, then constructs snakes (or contours) by grouping edge elements and feeds the shape analysis. The top-down one uses shape analysis, by comparing the object model with the extracted snakes, to guide/prune the search for other snakes. The optimizations are based on Dijkstra algorithm and further pruning of this algorithm is obtained by ``integration by parts''. Our approach is general enough to handle three dimensional objects, but our focus here is on two dimensional contours.