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。
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。
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。
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。
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；
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。
A method of subtle expression recognition based on hybrid features and classifier tree is presented in this paper.
因此提出了基于混合特征和分类树的细微表情识别方法。
In this paper, a multimodal error correction technique is introduced for handwritten mathematical expression recognition.
提出一种用于纠正手写数学公式识别错误的多通道技术。
Following this topic, we research the key Algorithms for smile recognition and multi-Expression recognition in this paper.
本文以人脸表情识别方法为主题，研究了用于笑脸识别与多类表情识别的关键算法。
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 experimental result proves the superiority of the 2d MB-LGBP composite features to MB-LGBP and some other popular features in expression recognition.
实验结果证明了二维mb -LGBP特征相比于MB - LGBP以及其他一些主要的表情识别特征的优越性。
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。
In this dissertation, it will focus on time expression recognition, which is one of the most important directions within named entity recognition research area.
本文所研究的时间表达式识别，就是命名实体识别领域一项基础而重要的任务。
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。
For implicit temporal expression recognition, witch is also called as Chinese situation analysis. The Bayes classification is used for Chinese verb classification.
对隐含时间表达的识别，即汉语情态的分析，采用贝叶斯分类法进行动词分类和情态分类。
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。
Nowadays, expression recognition has become an active topic in pattern recognition and machine vision community. More and more researchers have focused on this domain.
目前表情识别已经成为模式识别和机器视觉研究领域的一个活跃分支，越来越多的研究者开始关注这个领域。
To recognize the Chinese temporal expression, we divide the task into two sub-tasks: the explicit temporal expression recognition and the implicit temporal expression recognition.
在汉语时间表达识别中，主要内容分为两部分：明显时间表达的识别和隐含时间表达的抽取。
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。
It finds applications in various areas, such as face detection, face recognition, gesture recognition, expression recognition, face image compression and reconstruction, and face cartoon.
它可广泛应用于人脸跟踪、人脸识别、姿态识别、表情识别、头部像压缩及重构、脸部动画等领域。
The size normalization of notations is a common pretreatment method in mathematical expression recognition, and it has a great significance to enhance the efficiency of notation recognition.
符号的大小归一化是数学表达式识别的一种很常见的预处理方法，它对于提高符号的识别率具有重要的意义。
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。
If the application has a dynamic object or if several versions of the application are slightly different, correct versions of an object, replace the recognition property with a regular expression.
如果应用拥有动态对象或应用的多个版本之间有细微的差别，为了获得对象的正确版本，可以使用正则表达式来替换识别属性。
If the application has a dynamic object or if several versions of the application are slightly different, correct versions of an object, replace the recognition property with a regular expression.
如果应用拥有动态对象或应用的多个版本之间有细微的差别，为了获得对象的正确版本，可以使用正则表达式来替换识别属性。
应用推荐