Human Action Recognition Using Geometric Parameter Features and a Radial Basis Function Neural Network

Abstract

A new biological method is proposed for the recognition of human actions based on geometric parameter features and the Radial Basis Function (RBF) neural network. First, the shape feature of the binary image sequences of a human body is calculated. Next, the geometric parameter features of the shape are computed based on the binary image sequences by using a vector which consists of the region and the shape feature. An improved RBF neural network classifier is then employed to identify the human action through posture recognition. To increase the learning efficiency of the neural network, improvements to the RBF learning algorithm are suggested to train the neural network. Experimental results indicate that the proposed scheme can effectively classify human actions and achieve a superior recognition rate.