The paper discusses facial expression recognition based on image algebraic characters. First, eyes and mouth are segmented from the facial expression image and variant moments and singular value feature vectors of eyes and mouth are extracted.
探讨了图像代数特征在面部表情识别中的应用，首先对面部表情图像进行了分割，得到眼睛和嘴巴区域，然后分别对眼睛和嘴巴区域提取不变矩和奇异值特征向量，并进行Fisher线性判别分析，最后训练了支持向量机分类器。
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Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
The algebraic feature extraction of images and the authors' research work on singular value vectors as a kind of algebraic features of images are emphasized.
重点介绍了图像的代数特征抽取以及作者关于奇异值特征矢量作为图像的一种代数特征方面的研究工作。
A feature extraction method of high-range-resolution radar profiles, which takes advantage of wavelet packet transform and modified SVD (singular value decomposition) was proposed.
提出了基于小波包变换和改进奇异值分解的高分辨雷达目标一维距离像特征提取方法。
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