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Facial Expression Feature Selection Based on Rough Set

机译:基于粗糙集的面部表情特征选择

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An improved reducing algorithm for rough set attributes has invented for answering the question of the excessive features vector dimensions. It obtains the local feature vector through geometric feature points. By introducing the rough set and improved reducing algorithm that it is able to select optimally among the existing expression features, also clipping the redundancy and useless information for the selection of expression feature. The experiment has showed that, this method has demonstrated high level of validity for its more convenience, higher recognition rate and more efficiency.
机译:为了回答过大的特征向量维数的问题,发明了一种改进的用于粗糙集属性的归约算法。它通过几何特征点获得局部特征向量。通过引入粗糙集和改进的归约算法,该算法能够在现有表达特征中进行最佳选择,同时也减少了冗余和无用的信息,以选择表达特征。实验表明,该方法具有更多的便利性,更高的识别率和更高的效率,显示出较高的有效性。

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