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The background modeling for the video sequences using Radial Basis Function neural network

机译:基于径向基函数神经网络的视频序列背景建模

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This paper an adapted background subtraction system based on Radial Basis Function neural network is given. In the suggested system for each background pixel a two-state machine is considered in which the RBF1 neural network is used for crossing between different states of the machine. In suggested system is flexible to light changes and very few movements of background object and the presence of new object in the background and other challenges mentioned in the field of estimate the background. The test are down on image group of Wallflower data set, the obtained result confirm the efficiency of the suggested solution.
机译:给出了一种基于径向基函数神经网络的自适应背景减法系统。在建议的系统中,对于每个背景像素,考虑了一种两状态机,其中使用RBF 1 神经网络在机器的不同状态之间交叉。在所建议的系统中,其对于光的变化是灵活的,并且背景物体的移动很少,并且背景中新物体的存在以及在估计背景领域中提到的其他挑战。该测试基于Wallflower数据集的图像组,获得的结果证实了所建议解决方案的效率。

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