用统计学的方法，等角度间隔地计算归一化步态轮廓图像各像素点至质心距离的均值与方差，并用其构造步态识别的特征向量。

Using statistical methods to calculate the Angle interval mean and variance of pixels to centroid distance of the normalized gait silhouette images, and construct them as a feature vector.

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并对该特征向量进行对数归一化，将归一化的特征向量作为径向基函数（RBF）神经网络的输入，在此基础上进行识别，达到较好的识别效果。

The normalized vector is used as the input of RBF NN, and target recognition is performed based on this, which leads to a satisfactory recognition result.

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该方法包括以下几个步骤：（1）先将训练样本归一化，再利用PCA变换进行降维，获得样本特征向量；

The proposed method is composed of the following three parts:(1) The feature space is reduced by the PCA(the principal component analysis) on the normalized input spectra;

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该方法包括以下几个步骤：（1）先将训练样本归一化，再利用PCA变换进行降维，获得样本特征向量；

The proposed method is composed of the following three parts:(1) The feature space is reduced by the PCA(the principal component analysis) on the normalized input spectra;

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