The results can be applied to the analysis of 3d face feature and design of oxygen mask and face-protecting equipment.
所获得的结果可用于分析面部三维形态特征，并为供氧面罩等面部防护装具的造型设计提供依据。
Eigenfaces is one of the most popular method in face feature extraction and recognition.
特征脸法是一种常用的人脸特征提取和识别方法。
In this paper, a method based on within-class average faces of two-dimensional PCA is proposed for face feature extraction.
该文提出了一种基于二维pca的类内平均脸方法进行人脸的特征提取。
A facial expression recognition system contains face detection, face feature extraction, feature selection and expression classification.
表情识别系统包括人脸检测、人脸特征提取、特征选择以及表情分类等几部分。
Based on principal component analysis (pca) Face Feature Extraction MATLAB implementation.
基于主元分析(pca)的人脸特征提取MATLAB实现。
Based on principal component analysis (pca) Face Feature Extraction MATLAB implementation.
基于主元分析(pca)的人脸特征提取MATLAB实现。
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