基于双层卷积神经网络的步态识别算法

Gait recognition based on double-layer convolutional neural networks

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.

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.