“ Rather than explicitly modeling the values of all
the pixels as one particular type of distribution, we
simply model the values of a particular pixel as a mixture of Gaussians.”

Chris Stauffer 与 W.E.L Grimson $^{[1]}$在1999年首先将高斯混合模型应用到了背景提取上，针对图像中的像素建立高斯混合模型，不同高斯模型分别对应着前景与背景。在此基础上匹配新出现的像素，根据匹配到的高斯模型来确定是前景还是背景。

Pfinder

#### Reference:

[1] Stauffer, Chris, and W. Eric L. Grimson. “Adaptive background mixture models for real-time tracking.” Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149). Vol. 2. IEEE, 1999.
[2] KaewTraKulPong, Pakorn, and Richard Bowden. “An improved adaptive background mixture model for real-time tracking with shadow detection.” Video-based surveillance systems. Springer, Boston, MA, 2002. 135-144.
[3] Zivkovic, Zoran, and Ferdinand Van Der Heijden. “Efficient adaptive density estimation per image pixel for the task of background subtraction.” Pattern recognition letters 27.7 (2006): 773-780.