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 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。
To satisfy the need of video moving object locating in intelligent video surveillance scenes, video moving object locating technology based on nonparametric kernel density estimation is proposed.
针对智能视频监控场合对视频运动目标定位的需求，本文提出了一种基于非参数核密度估计的视频运动目标空域定位技术。
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