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。
This paper proposes two high performance facial expression recognition methods.
文中提出了两种高效的人脸表情识别算法。
Then current facial expression recognition technologies are roughly introduced.
然后对近期人脸表情识别的方法进行了分类综述。
Facial expression recognition is an active research area in pattern recognition.
人脸表情识别是模式识别领域中一个非常活跃的研究方向。
Human facial expression recognition is a very important but also difficult subject.
人脸表情识别是模式识别中一个非常重要却十分复杂的课题。
In this paper, Facial Expression Recognition of the four main areas were carried out research work.
本文在人脸表情识别的四个主要环节上均进行了研究工作。
Now, there're many methods of facial expression recognition, but research on expression intensity measurement hasn't been developed.
目前已有多种面部表情识别方法，但是对表情强度的度量并没有充分展开。
As an important part of the technology for human-machine interface, facial expression recognition have drawn much attention recently.
人脸表情识别作为智能化人机交互技术中的一个重要组成部分，近年来得到了广泛关注。
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。
It makes a detailed introduction to expression pre-processing methods, and looks forward to the future of facial expression recognition research.
同时对表情处理的方法进行了介绍，展望了表情识别未来的研究重点。
The human-head portrait robot system H&F ROBOT-II with vision, facial expression recognition and representation functions was designed and developed.
本文设计并研制了具有视觉、表情识别与再现功能的仿人头像机器人H&FROBOT-II系统。
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。
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 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。
In recent years, the reasons for renewed interest in facial expression recognition are multiple, but mainly due to people have more interest about human computer interaction (HCI).
近年来，随着人们对人机交互兴趣的增加，表情识别逐渐成为一个研究热点。
Recently, many novel methods are applied in the facial expression recognition such as Artificial Neural Networks, Support Vector Machines, Wavelet Analysis, Hide Markov Model and Optical Flow, etc.
近来，很多新的算法被应用在表情识别当中来，如：人工神经网络、支持向量机、小波分析、隐马尔可夫链模型和光流等。
A video camera connected to facial recognition software gave the robot feedback: When it made a movement that resembled a "real" expression, it received a reward signal.
一台与面部表情识别软件相连的摄影机给机器人反馈信号：当机器人做出一个类似于“现实的”表情时，摄影机就会收到动作信号。
Objective: To study the characteristics of executive function and its possible mechanism by Wisconsin card sorting test (WCST) and recognition of dynamic facial expression in patients with depression.
目的：通过威斯康星卡片分类测试(WCST)及动态面部表情识别任务，探讨抑郁症执行功能障碍特征及可能机制。
Therefore the automatic recognition technology of facial expression has received the researchers' extensive concern.
人脸表情自动识别技术因而受到了研究者们的广泛关注。
Objective:To explore neural correlates for the explicit recognition of dynamic facial expression in male major depressed patients using event-related functional magnetic resonance imaging.
目的：抑郁症患者存在负性认知模式，本研究旨在探讨男性抑郁症患者识别动态面部表情情绪偏向性的神经基础。
This study discusses, mainly through the means of behavior experiment, the influence of the facial arrangements on the recognition of partial-face expression.
本研究主要采用行为实验探讨面孔呈现顺序对局部表情识别产生的影响。
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。
Facial expression; Expression recognition; Expression representation; Robot head mechanism;
面部表情； 表情识别； 表情再现；机器人头部机构；
However, because of the complex facial structure, the diverse facial expression and the changing light intensity, face recognition is still being recognized as a challenging research.
但人脸图像中表情、姿态、光照度等内外在因素皆多变，使得该研究至今仍颇具挑战性。
However, because of the complex facial structure, the diverse facial expression and the changing light intensity, face recognition is still being recognized as a challenging research.
但人脸图像中表情、姿态、光照度等内外在因素皆多变，使得该研究至今仍颇具挑战性。
应用推荐