This is a simple design of the Gaussian kernel source code.
这是一个简单的高斯核设计源代码。
The Gaussian kernel mean-shift algorithm which is deduced from kernel density estimation has not been widely employed in applications because of its low convergence rate.
由核密度估计推导获得的高斯核均值漂移算法因收敛速度慢在应用中效率不高。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通过相隔固定的帧差值阅值化得到背景样本值，并采用高斯核密度估计方法计算背景灰度的概率密度函数。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通过相隔固定的帧差值阅值化得到背景样本值，并采用高斯核密度估计方法计算背景灰度的概率密度函数。
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