A smart stochastic approach for manifolds smoothing

In this paper, we present a probabilistic approach for 3D object’s smoothing. The core idea behind the proposed method is to relate the problem of smoothing objects to that of tracking the transition probability density functions of an underlying random process. We show that such an approach allows for additional insight and sufficient flexibility compared with existing standard smoothing techniques. In particular, we are able to propose a newer, faster, and simpler smoothing approach that retains and enhances important manifold features. Furthermore, it is demonstrated to improve performance over existing smoothing techniques.