Multi-module minimization neural network for motion-based scene segmentation

A competitive learning network, called Multi-Module Minimization (MMM) Neural Network, is proposed for unsupervised classification. The objective is to provide a general framework to divide a set of input patterns into a number of clusters such that the patterns of the same cluster exhibit any pre-specified similarity measure (i.e. not limited only to RBF). As an example of non-RBF measure, a motion-based segmentation problem is considered. Simulation results demonstrate that the MMM neural network does capture different motions and yield fairly accurate segmentation and motion-compensated frames.