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An improved mixture of Gaussians model based on color and depth data

机译:基于颜色和深度数据的高斯模型的改进混合

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In the traditional background subtraction algorithms based on color, in the special critical situation, such as face the challenges of shadows, color camouflage, illumination changes, they can't achieve good results. But depth data can solve such problems effectively, because depth sensor operating normally in the scene. We proposed an improved mixture of Gaussian model algorithm based on color and depth data in this paper, and use a new decision-making method to fuse results. In order to ensure the stability of the model, we have special treatment of the ADO area. We test our method in three datasets, the results show that proposed approach obtain good results.
机译:在传统的背景减法算法基于颜色,在特殊的危急情况下,如面对阴影,颜色伪装,照明变化的挑战,他们无法达到良好的效果。但深度数据可以有效地解决这些问题,因为深度传感器正常在场景中运行。我们提出了一种基于本文颜色和深度数据的高斯模型算法的改进的混合,并使用新的决策方法来融合结果。为了确保模型的稳定性,我们有特殊的ADO区域。我们在三个数据集中测试我们的方法,结果表明,提出的方法获得了良好的效果。

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