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An improved method for emotion detection using weighted Gabor filter and radial basis Function kernel

机译:加权Gabor滤波器和径向基函数核的情感检测改进方法

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摘要

Human emotion detection plays an important role in the human-computer interaction. In this paper, the emotions are detected on segmented image using low dimension weighted Gabor filter bank. The segmentation reduces the space domain and only those facial features are focused that reflects expressions accurately. The classification of selected features values classifies through a RBF network. The experimental results show that by the selection of optimal features, the computational complexity reduces significantly.
机译:人的情感检测在人机交互中起着重要的作用。在本文中,使用低维加权Gabor滤波器组在分割图像上检测情绪。分割减少了空间域,并且仅聚焦那些可以准确反映表情的面部特征。所选要素值的分类通过RBF网络进行分类。实验结果表明,通过选择最优特征,计算复杂度大大降低。

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