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.
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。
For example, it costs more for storage and the distance computation is quite complex. With the number of images grows, it will be unsuitable for vector based image feature to stay in memory.
当图像数量增长到一定数量后，基于浮点矢量形式表示的图像特征就不适合放置在内存中，欧氏距离的计算也将造成较大的时间开销。
Float vector based image feature has high dimension and usually makes use of Euclidean distance as its similarity definition.
浮点矢量图像特征维数较高，且通常以欧氏距离作为矢量之间的相似度定义。
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