特征脸法是一种常用的人脸特征提取和识别方法。
Eigenfaces is one of the most popular method in face feature extraction and recognition.
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.
一般的人脸特征提取方法都可以将该方法作为提高效率的预处理操作。
This method is characterized by its low operation cost, high efficiency and accuracy.
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。
A facial expression recognition system contains face detection, face feature extraction, feature selection and expression classification.
视觉交互是自然人机交互的重要组成部分，而人脸特征提取则是视觉交互成功的关键。
Vision interaction is one of important aspects of human-computer interaction, and the facial feature extraction is crucial to vision interaction.
一般来说，人脸识别系统包括人脸检测、特征点定位、图像预处理、人脸特征提取以及人脸识别。
Generally speaking, the face recognition system consists of face detection. feature piont location, image pre-processing, feature extraction and face recognition.
其中人脸特征提取采用了奇异值分解和主分量分析法，身份验证则采用了以类内平均距离为判据的算法。
Here, we use the singular value decomposition and principal component analysis for facial feature extraction, using the average distance category as discrimination on the basis of authentication.
该算法将人脸特征提取与图像复合相结合，无需3维人脸模型重建，自动合成具有源图像主要五官特征的结果图像。
This paper combines facial features extraction with image fusion algorithm, so that we can automatically obtain synthesis results without using 3d facial models.
另外，不管是人脸检测与分类，若有较好的人脸特征数据，即选取有效的人脸特征提取方法，是保证效果良好的前提。
In addition, whether face detection and classification, if a better face feature data are selected and effective method of face feature extraction is a prerequisite to ensure good results.
这里特征提取是人脸识别的关键环节，有效的人脸特征提取方法不仅有助于简化后续的分类器设计，而且能够提高识别率。
Feature extraction is the key to face recognition. An effective feature extraction method not only helps to simplify the classification of follow-up design, but also can enhance the recognition rate.
人脸面部特征提取是自动视觉翻译和人脸识别中的最关键的技术之一。
Facial features extraction is one of the essential techniques in automated visual interpretation and recognition of human faces.
提出了一种基于特征提取和验证相结合的人脸检测方法。
Based on facial features extraction and verification, we present a new human face detection method.
本文采用的技术包括：皮肤检测、人脸检测、目标区域分割、敏感图像特征提取、分类器设计及过滤器在浏览器上的实现等。
Some key techniques are included, such as skin detection, face detection, object area segmentation, image features extraction, the design of classifier and the implement of filter based on browser.
根据人脸图像的边缘梯度图提出了一种新的基于梯度向量流场的眼睛特征提取方法。
According to features of edge gradient maps of face images, a new eye feature extraction algorithm based on gradient vector flow field was proposed.
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。
In this paper, a method based on within-class average faces of two-dimensional PCA is proposed for face feature extraction.
人脸表情识别系统中的算法主要有图像处理算法、特征提取算法和分类算法。
The algorithms of facial expression recognition system mainly contain images' preprocessing algorithms, feature extraction algorithms and classification algorithms.
该方法首先利用核主元分析对人脸图像进行特征提取，然后依据支持向量机与最近邻准则对所提取的核主元特征进行分类识别。
Firstly KPCA is used to extract the features of human face image, and then SVM combined with the nearest distance rule is used for classification, which depends on the kernel principal components.
并在特征提取环节，提出CSVD算法与非负矩阵因子算法特征数据相融合的人脸识别算法。
And in the feature extraction process, a new face recognition method based on CSVD and non Negative Matrix Factorization (NMF) is presented.
本文对多种生物特征综合识别系统的特征提取算法进行研究，即人脸和指纹综合识别系统。
This dissertation research on the feather extracting algorithm of the technologies of identity recognition based on multi-biometrics which is face recognition combined with fingerprint recognition.
因此对于人脸识别中的特征提取来说，不仅要检测出这些特征，而且要准确地加以定位。
Therefore, feature extraction for face recognition, not only to detect these features, but also to accurately locate.
若干标准人脸数据集和人工数据集上的实验表明ILDA在特征提取方面的有效性。
Numerical experiments on ORL facial database and man-made datasets show ILDA achieves good performance in feature extraction.
本文提出一种新的特征提取方法，人脸图像在2dpca投影的基础上进行B2DLDA投影提取出人脸特征。
This paper proposed a new feature extraction method, that face feature is extracted based on projections on the 2dpca and B2DLDA.
提出了一种利用模板匹配与遗传算法的人脸图像特征提取的方法。
A method of extracting eye and mouth features from facial images using deformable templates and genetic algorithms is described.
人脸识别是一种崭新的生物特征识别技术，面部图像特征提取是其研究的难点、热点问题。
Face recognition is a new biologic technology of recognition, while the feature abstract of face is the most difficult and popular problem in these area.
一个完整的人脸识别系统包括人脸检测、特征提取、以及匹配识别。
A complete Human Face Recognition System should include Human Face Detection, Feature Extraction, and Match Recognition.
提出一种全自动面部特征提取算法模型和三维人脸从侧面和正面的正交的人的脸被标定相机。
We present a fully automated algorithm for facial feature extraction and 3D face modeling from a pair of orthogonal frontal and profile view images of a person's face taken by calibrated cameras.
本论文结合几何特征提取方法和神经网络方法，提出了一种新的人脸识别方法。
A new approach to face recognition combining geometry feature distilling and neural networks methods is proposed.
人脸识别主要包括三方面的内容：人脸检测与定位，特征提取，分类与识别。
Face recognition includes three parts: face detection and localization, feature extraction and classification.
本系统包括视频捕获模块，人脸检测模块，特征提取模块及人脸识别模块。
This system includes video capture module, the face detect module, the feature extraction module and the face recognition module.
本系统包括视频捕获模块，人脸检测模块，特征提取模块及人脸识别模块。
This system includes video capture module, the face detect module, the feature extraction module and the face recognition module.
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