To the weight update of Latent Semantic Analysis(LSA)model, this paper proposes an adaptive weight update algorithm based on Bayesian theory(ALSAB).
针对潜在语义分析(LSA)模型的权重更新问题,提出了一种基于贝叶斯理论的自适应权重更新算法ALSAB。
Taking the method of adaptive Gaussian mixture method can make model for background meanwhile it is a difficult point to maintain and update background model.
采用自适应高斯混合方法为背景建模的难点是对背景模型的维持与更新。
Experimental results are presented to demonstrate that our algorithm can be adaptive to the appearance changes as well as occlusions and is more robust than the total model update strategy.
实验结果表明,该算法既能较好地适应目标的外观变化,又具有较强的抗遮挡能力,比整体模板更新算法具有更好的鲁棒性。
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