A robust and adaptive appearance model is proposed, in which the value of each pixel over time is modeled by a mixture of Gaussians.
提出一种鲁棒自适应表面模型,该模型中每个像素值的变化过程由一混合高斯分布描述。
When estimating the target state, particle filter is adopted, and the observation model is designed based on the adaptive appearance model.
在估计目标状态时,采用了粒子滤波算法,设计了基于自适应表面模型的观测模型;
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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