facial feature

On the basis of image segmentation by complexion and gray information, some rough facial feature contours can be outlined by seed-filling the non-complexional regions.

根据肤色和灰度信息，在图像分割的基础上，利用种子填充技术获得面部各非肤色特征的轮廓初值；

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According to the key witnesses, a peculiarly big nose is the criminal's most memorable facial feature.

根据重要目击者的描述, 特别大的鼻子是这个犯人面部的最令人难忘的特征.

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China has unveiled the world's first ATM with a built-in facial recognition feature.

中国近日发布了全球首款内置人脸识别功能的自动柜员机（ATM）。

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A facial feature point localization and facial expression recognition system is developed.

设计了一个特征点定位和表情分析系统。

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Based on the new algorithm, human facial feature extraction algorithm is proposed.

然后提出一种人脸特征抽取算法。

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This paper describes a method semi automatic facial feature tracking in video sequences.

文中提出一种跟踪人脸特征点的方法.

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Facial feature extraction is import part in face recognition.

人脸面部特征的提取是人脸识别技术的重要环节.

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facial feature extraction of front face based on geometrical characters

基于几何特征的人脸正面图像特征提取

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Facial Expression Recognition System Based on Multiple Feature Integration

融合人脸多特征信息的表情识别系统

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Facial expression feature extraction based on Fisher linear discriminant analysis ( LDA).

基于Fisher线性判别分析的人脸表情特征提取。

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Accurate localization of facial feature points based on random forest classifier

基于随机森林的人脸关键点精确定位方法

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A peculiarly pointed chin is his most memorable facial feature.

古怪的尖下巴是他最有特点的面部特征.

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This paper focus on the feature dimension reduction method of combination of PCA and LDA, finally recognize the facial expression information using HMM.

本文研究了PCA和LDA结合的特征降维方法，最后用HMM进行面部表情信息识别。

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The gainer of 2001 Nobel economics award Stiglitz believe that: there are two things that will influence the process and change the facial feature of the world, one is the development of the high technology of the USA, another is the progress of urbanization of China.

2001年诺贝尔经济奖获得者斯蒂格列茨认为，21世纪影响世界进程和改变世界面貌的有两件事：一是美国高科技的发展；二是中国的城市化进程。

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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。

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many physical indicators exist, with facial feature alterations being the most prominent.

还有许多身体指标存在，其中面部特征的改变最为显著。

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With the facial feature information of users, machines can understand behaviors and mental state of users.

借助于用户的人脸特征信息, 机器能够理解用户的动作行为和感知用户的精神状态.

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based on linear combination model, a new facial feature extraction method is proposed.

为了实现人脸图像特征的自动检测，提出了一种基于线性组合模型的人脸特征检测新方法。

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A scheme to estimate facial feature points and expression regions from coarse to fine is proposed.

提出了一种从粗糙到精细估计脸部特征点和表情区域的方法.

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In order to build the real-time facial expression recognition system, expression feature extraction using fast and accurate facial feature points localization is an effective method.

为了构建实时的人脸表情分析系统，本文利用快速准确的人脸特征点定位方法来获取表情特征，进而对表情特征进行分类，从而识别出人脸表情。

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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.

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。

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Definition of facial feature extraction affects direct rate of face recognition.

人脸特征提取的精确与否直接影响到人脸识别的正确率.

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