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Recognition of mixed facial expressions by neural network

机译:神经网络识别混合表情

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Deals with a neural network method for the machine recognition of mixed facial expressions by decomposing mixed facial expression into 2 or 3 components of 6 basic ones. The authors obtain the facial images, which show mixed facial expressions, from video tape recorded facial images and from the information of facial expressions in terms of the (x,y) coordinates of facial characteristic points. Then the position information of facial image is generated for 19 clients, and is used for the neural network training and recognition test. The recognition test is done by inputting the facial information, not being used in training the neural network, to the trained neural network. The recognition results obtained by the neural network are compared with those by humans. The neural network method is found to give a rather high agreement rate of about 70% compared with those obtained by humans.
机译:通过将混合面部表情分解为6个基本面部表情的2或3个分量,来处理用于混合面部表情的机器识别的神经网络方法。作者从录像带录制的面部图像以及根据面部特征点的(x,y)坐标的面部表情信息中获得了显示混合面部表情的面部图像。然后为19个客户生成面部图像的位置信息,并将其用于神经网络训练和识别测试。通过将未在训练神经网络中使用的面部信息输入到训练后的神经网络中来完成识别测试。将神经网络获得的识别结果与人类的识别结果进行比较。与人类获得的神经网络方法相比,发现神经网络方法具有相当高的一致性,约为70%。

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