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bstract — Extracting moving objects from background is a critical step for computer vision applications. GMM based algorithms have become the most commonly used technique for background subtraction in video sequence. However, it is not always easy to establish efficient and accurate background model with fast convergence rate. In this paper, an effective scheme was proposed to improve the convergence rate of Adaptive-K Gaussian Mixture Model (AKGMM). The AKGMM algorithm altered the dimension of
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