Recognition of human action using boosting method and RBF neural network
YE Yin-lan · Computer Engineering and Applications Journal · 2008
A novel method is proposed for recognition of human action based on improved boosting RBF neural network.In the proposed method,normalized motion history image for motion representation is valued.Statistical descriptions are then computed from motion history image using Zernike moment-based features,then adaboost method is proposed for adaptive select feature.Then RBF neural network is used to class the human action.In order to improve the precision of the RBF neural network for recognition of human action,a weight-adjusting-based method is proposed to improve Boosting method.Experiment results have shown good recognition performance of our method.