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H. Kim, D. Kim and S. Yang, “An Efficient Model Order Selection for PCA Mixture Model,” Pattern Recognition, 2003, pp. 1385-1393.

has been cited by the following article:

• TITLE: On Segmentation of Moving Objects by Integrating PCA Method with the Adaptive Background Model

  AUTHORS: Noureldaim Emadeldeen, Mohammed Jedra, Noureldeen Zahid

  KEYWORDS: Pixels; Gaussian Mixture Model; Principle Component Analysis; Background Model; Noise Process; Segmentation

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.3 No.3, August 31, 2012

  ABSTRACT: Tracking and segmentation of moving objects are suffering from many problems including those caused by elimination changes, noise and shadows. A modified algorithm for the adaptive background model is proposed by linking Gaussian mixture model with the method of principal component analysis PCA. This approach utilizes the advantage of the PCA method in providing the projections that capture the most relevant pixels for segmentation within the background models. We report the update on both the parameters of the modified method and that of the Gaussian mixture model. The obtained results show the relatively outperform of the integrated method.