现代科学仪器Issue(2)：29-32,36,5.
基于脉冲神经网络的人体动作识别
Human Action Recognition Based on Spiking Neural Networks
摘要
Abstract
In order to improve the accuracy of human action recognition and accelerate the recognition speed,this paper investigates the question of extracting feature from visual cortex for representing human actions,and proposes that integrate and fire neuron model was used to simulate the V1 neurons.According to the characteristic of spiking output,the entropy of mean firing rate of each neuron formed a feature vector,and Support Vector Machine（SVM） was used to classify different act.We compared our results with Escobar model.on the Weizmann action database.As a conclusion,we convinces that this method is more effective than the model of Escobar for human action recognition.关键词
初级视觉皮层/脉冲神经元/脉冲序列Key words
Visual cortex/Spiking neural model/Spike trains分类
机械制造引用本文复制引用
黄丽鸿,高智勇,刘海华..基于脉冲神经网络的人体动作识别[J].现代科学仪器,2012,(2):29-32,36,5.基金项目
国家自然科学基金项目 （）
