研究人员还指出，狗将对人脸作为一个整体进行扫描是为了感知人们的感受，而不是只专注于某个特定特征。
The researchers also note that dogs scan faces as a whole to sense how people are feeling, instead of focusing on a given feature.
传统上，用计算机进行人脸识别是基于局部区域的特征例如眼睛、鼻子的形状，或者嘴巴宽度等。
Traditionally, computer face recognition is based on such factors as the characteristics of the eye region, the shape of the nose, or the width of the mouth.
软件能够为人脸建立一套演算法，通过度量来记录眼睛、鼻子和嘴巴的特征。
The software works by creating an algorithm of the face - a measurement of the arrangement of features including the eyes, nose and mouth.
人们通常会去注意这张照片同他们以前可能看过的其他脸部照片相似的地方，而不会注意照片中人脸的特征。
Rather than seeing the unique features of the face, people tend to focus on similarities with other mugshots they might have seen.
一般人都认为眼睛是人脸的焦点部位。眼睛是首先被注意到的面貌特征。
Common wisdom has it that the eyes are the focal point of the face and they are the features that draw attention first.
这样就消除了人们识记人脸时经常依靠的身体显著特征，迫使实验对象仅仅依靠主要面部特征来识别，而这正是Steeves和她的团队想要测试的技能。
This eliminated physical landmarks people often use to remember faces and forced the subjects to rely on major features alone, which was the skill Steeves and her team were trying to test.
计算机人脸识别技术是一种重要的基于生物特征的人类身份识别技术。
The machine recognition of faces is one of the most important identification recognition techniques based on biological features.
实现了一种基于矩形特征的人脸检测算法。
A face detection algorithm is implemented based on rectangle features.
根据人的面部器官所遵循的比例关系，将人脸划分为若干个窗口，在窗口内对面部特征点进行检测。
We segment the face image into several "Windows" according to the prOportion relationship of organs and detect the feature points in each window.
本文主要研究目前较为流行的基于统计学习理论的分类方法——支持向量机方法(SVM)，以及小波变换提取特征的方法，将其用于人脸检测。
This paper mainly make research on classify methods based on statistical theory, support vector machine (SVM), and feature extraction method-wavelet transform, and using them in human face detection.
之前，这种人脸特征被认为是为了适应那些难以咀嚼的食物，比如坚果。
The characteristics were previously thought to be adaptations for a diet of hard-to-chew foods, such as nuts.
对传统的特征脸方法进行改进，可以提高人脸正确识别率、缩短识别时间。
Modify the Eigenfaces method can improve the face correct recognition rate and reduce the recognition time.
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.
人脸识别是生物特征识别技术中一个非常活跃的课题，取得了很多研究成果。
Face recognition is an active subject in the area of biometrical recognition technology, and lots of achievements have been obtained.
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.
对于复杂的人脸模式，脸部特征定位是人脸自动识别技术的关键。
Due the complex human face patterns, facial features localization is an important technique for automatic human face recognition.
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.
肤色特征是人体表面的重要特征，在人脸检测与识别、基于内容的不良图像过滤系统中有着重要的地位。
The feature of skin color is an important feature of human being, which plays a key role in human face detection and recognition, objectionable image filtering based on content, etc.
提出一种在分数层上对全局和局部特征进行融合的人脸识别方法。
This paper proposes a score level fusion method using both global and local features for face recognition.
说明：用 VC++编写的面部识别源程序，根据面部特征识别人脸，感兴趣的朋友可以看看！
Prepared with VC++ facial recognition source code, based on facial features to recognize human faces, and interested friends can see!
本论文主要研究DTCWT在纹理合成和人脸特征检测方面的应用。
This thesis mainly focuses on the application of DTCWT on texture synthesis and facial feature detection.
跟踪阶段用卡尔曼滤波器结合肤色特征跟踪人脸，如果跟踪失败，转入检测阶段。
In the tracking stage, track face using kalman filter and skin-color feature, if fail to track then turn into detecting stage.
提出利用最大相关最小距离将图像的纹理特征、高斯密度特征与人脸检测相结合的算法进行图像检索。
A new image retrieval method by using Max correlation min distance to combine together texture features, Gaussian density characteristics and face detection of images for image retrieval is presented.
给出了一种基于离散傅里叶不变特征的人脸识别方法。
A face recognition method based on discrete Fourier invariant features is presented.
本文在总结和分析现有人脸检测技术的基础上，重点研究了基于矩形特征的人脸检测技术及以此为基础并结合运动信息的动态人脸检测技术。
Relying on the analysis of existed face detection techniques, this paper mainly describes face detection based on rectangle feature and dynamic face detection combined with motion information.
人脸轮廓提取是人脸特征检测和人脸识别等人脸图像分析的重要前提。
Face contour extraction is a significant precondition of facial image analysis such as facial features detection and face recognition.
人脸特征的自动提取是人脸自动识别过程中至关重要的一个环节。
The extraction of face features is an important part in the process of face automatic recognition.
在人脸跟踪领域，本文对比了当前几种主要的相似度匹配方法，采用了一种基于特征空间模型的人脸跟踪方法。
In the field of human face tracking, we contrast several main similarity methods nowadays, and adopt a method of human face tracking based on feature space model.
许多重要的识别技术假设人脸的脸部特征已被精确定位，因此人脸及其特征的精确定位是人脸处理系统的关键步骤。
Since most recognition techniques suppose the positions of facial features are located accurately, the fine location of facial features is crucial steps in most face processing system.
基于小波分解提取人脸特征技术和多分类支持向量机模型，提出了一种新的准正面人脸识别算法。
This paper presents a novel algorithm for quasi-frontal face recognition based on the wavelet decomposition technique and a multi-class Support Vector Machine (SVM) model.
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