| 基于双层卷积神经网络的步态识别算法 |
| |
| 引用本文： | 王欣,唐俊,王年.基于双层卷积神经网络的步态识别算法[J].安徽大学学报(自然科学版),2015(1):32-36. |
| |
| 作者姓名： | 王欣 唐俊 王年 |
| |
| 作者单位： | 安徽大学 电子信息工程学院,安徽 合肥,230039 |
| |
| 基金项目： | 国家自然科学基金资助项目(61172127)；高等学校博士学科点科研基金资助项目(20113401110006)；安徽省高校优秀青年人才基金资助项目(2012SQRL0172D)；安徽省自然科学基金资助项目 |
| |
| 摘 要： | 提出运用双层卷积神经网络模型实现基于足底压力图像的步态识别方法.首先,对足底压力数据采集系统采集的图像作相应预处理;然后,用双层卷积神经网络模型学习得到足底压力图像的单层和双层卷积特征;最后,将卷积特征训练分类器得到分类结果.实验结果验证了该算法的有效性.
|
| 关 键 词： | 卷积神经网络 足底压力图像 数据采集系统 深度学习 步态识别 |
Gait recognition based on double-layer convolutional neural networks |
| |
| WANG Xin,TANG Jun,WANG Nian.Gait recognition based on double-layer convolutional neural networks[J].Journal of Anhui University(Natural Sciences),2015(1):32-36. |
| |
| Authors: | WANG Xin TANG Jun WANG Nian |
| |
| Abstract: | This paper proposed an algorithm of gait recognition using double‐layer convolutional neural networks ( D‐CNN ) and plantar pressure image . Firstly , the preprocessing of the evaluated images from the plantar pressure test system was implemented .Secondly ,convolution features were learned from single and double layer of convolutional neural network model . Finally ,convolution features were used to train the SVM classifiers and obtain the classification results .The experimental results demonstrated the effectiveness of the proposed method . |
| |
| Keywords: | convolutional neural networks plantar image data acquistion system deep learning gait recognition |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
