Active Appearance Models (AAMs) is an effective method of facial recognition and facial feature location, and has become a research hotspot in image processing areas.
主动外观模型是进行人脸面部特征定位和人脸识别的有效方法，近年来已成为图像处理等领域的研究热点。
In this paper a new method about face recognition is presented based on the regional distribution of facial geometric feature in China.
文中提出了利用人脸面部几何特征地理区域分布的差异性进行人脸识别的新方法。
Adopt a method of order scoring in the feature matching, improve the rate of facial recognition.
在最后特征比对中采用了排位计分法和特征值加权等算法，有效的提高了系统的识别率。
This paper examines the research situation on face image detection and recognition and designs a facial feature automatic extract system.
对人脸图像检测与识别技术的研究现状进行简要论述，并自行设计一个人脸特征自动提取系统。
At first we propose a new algorithm for face recognition. And then, we can find the advantage of using this approach in facial feature extraction through the analysis of related experiment results.
先提出一种人脸识别的算法，然后通过实验数据分析，得出这种算法更能有效提取人脸特征。
The algorithms of facial expression recognition system mainly contain images' preprocessing algorithms, feature extraction algorithms and classification algorithms.
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。
Facial expression recognition is an effective and realizable feature in them.
其中的人脸表情识别是一种有效且可行的特征。
Facial feature points localization takes an important role in the face recognition, facial expression analysis, cartoon face synthesis, etc.
人脸特征点的定位在人脸识别、人脸表情分析以及卡通人脸生成等方面具有非常重要的作用。
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。
Facial feature point location is one of the fundamental and crucial problems in the field of facial recognition, computer vision and graphics.
人脸面部的关键特征点定位既是人脸识别研究领域中的一个关键问题，也是计算机视觉和图形学领域的一个基本问题。
The extracting of facial feature and the facial expression state represented by all kinds of facial feature are important steps in facial expression recognition.
脸部特征的提取和各种特征所代表的表情状态是识别是脸部表情识别过程中的重要步骤。
The key algorithms of facial expression recognition are studied in this paper and we focus our attention on the research of methods for feature extraction.
本文在研究表情识别关键算法的基础上，将重点放在特征提取方法的研究。
A member of the audience asked if Google glass could use facial recognition to help a user identify someone they are talking to — a particularly alluring feature at an industry conference.
比如有一名观众就提问道，谷歌眼镜是否能加入面部识别功能，帮助用户确认眼前的人的身份——这个功能对于这样一次很多人参加的大会来说，的确是一个非常有吸引力的功能。
A member of the audience asked if Google glass could use facial recognition to help a user identify someone they are talking to — a particularly alluring feature at an industry conference.
比如有一名观众就提问道，谷歌眼镜是否能加入面部识别功能，帮助用户确认眼前的人的身份——这个功能对于这样一次很多人参加的大会来说，的确是一个非常有吸引力的功能。
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