Wang Shi-tong

Facial expression recognition using RBF neural network based on improved artificial fish swarm algorithm

Artificial fish swarm algorithm (AFSA) is a global optimization method proposed recently. After analyzing the disadvantages of AFSA, this paper introduced best-step operator and refined the prey behavior. An improved artificial fish-swarm algorithm for the RBF neural network and a model based on this method is developed. Finally the new algorithm is applied to the problem of expression recognition. The research indicates that the new algorithm has some advantages in terms of convergence performance, recognition rate and so on.

Using Mean-Shift to Improve Active Shape Model Search

In this paper we introduce a new method for locating shapes. The method is based on active shape model, and combining with mean shift to improve local search in the region around each landmark. Bringing new local descriptor and search strategy to active shape model search, mean shift can improve active shape model in both precision and speed.