A dynamic generating graphical model for point-sets matching

This paper presents a new dynamic generating graphical model for point-sets matching. The existing algorithms on graphical models are quite robust to noise but are susceptible to the effects of outliers. We investigated the influences of separators on point-sets matching in inference of graphical models theoretically and found that the separators that consist of outliers will interfere with message-passing, which will directly lead to failure of the existing methods. Because of this, in order to minimize the outliers in the separators, we propose a new algorithm for generating a graphical model and a corresponding Junction Tree for point-sets matching. A bi-mapping algorithm is also introduced to solve the problem of multi-mapping caused by outliers. Experiments were carried out on both synthetical data and real-world data with point-sets extracted by the Harris corner detector. The results show that the proposed algorithm is significantly more stable and possesses higher accuracy of point-sets matching, which can overcome the limitation of the sensitivity of outliers in the existing graphical models.