关键词: 粗糙集, 特征选择, 几何特征点, 表情分类

Abstract: In order to resolve the problem that the feature vector dimension is too high，rough set attribute reduction algorithm applied in expression features selection is advanced.It can acquire local expression features vectors using geometrical feature points method.Rough set theory is introduced，and the local expression features are optimized and selected with an attribute reduction algorithm of rough set.Redundant features and irrelated information to expression classification are also eliminated.Experimental results show that this method can be realized simply.High recognition rate and speed also indicate the effect of this facial expression features selection.

Key words: rough set, features selection, geometrical feature points, expression classification