姿态表情

首先介绍表现表情分为三种方式，面部表情、语言声调表情以及身体姿态表情。

First introduced performance expression is divided into three ways , facial expressions , tone of the language expression and posture expression .

珠儿依旧用她的食指指点着；眉间渐渐皱起；由于这姿态表情来自一个满脸稚气、甚至象婴儿般面孔的孩子，就给人印象尤深。

Pearl still pointed with her forefinger ; and a frown gathered on her brow ; the more impressive from the childish , the almost baby-like aspect of the features that conveyed it .

利用3D人脸建模的方法进行人脸识别有效地克服了2D人脸识别系统中识别率易受光照、姿态、表情影响的缺陷。

3D face modeling for face recognition overcomes the shortcoming effectively that the 2D face recognition is easily affected by the variation of illumination , pose and facial expressions .

3D面部识别是一种比较新的面部识别方法，主要是用来解决由于2D面部识别所带来的难以解决的人脸因姿态、表情、光照等因素而影响识别效率的一种有效方法。

3D face recognition is a relatively new face recognition method is primarily used to solve 2D face recognition as difficult to solve brought people face because of posture , facial expressions , illumination and other factors which affect the efficiency of identifying an effective way .

附加符号[字符]，特殊符号体态语是通过人的姿态和表情来传递信息的非语言符号。

Body language is the nonverbal sign which transmits information by human people 's posture and expression .

而三维人脸识别技术对光照、姿态及表情的变化鲁棒性较强，成为人脸识别技术研究的重要方向。

Instead , 3D face recognition technology is more robust to the illumination perturbation , and the variations of poses and face expressions .

并且拥有实时快速检测；无尺度、姿态、表情限制的优点。

Many advantages of real-time , fast detection and without the restrain of size , posture and expression are still possessed in the algorithm .

实验结果证明：系统对人脸图像的光照、姿态、表情变化等有较好的鲁棒性，在识别率和识别速度方面取得了理想结果。

Results prove that the system is robust to the illumination , pose and expression variations . The average recognition rate and speed is ideal .

然而，在非理想条件（如光照、姿态、表情等变化）下，自动人脸识别系统的性能还有待提高。

However , when it comes to the variant illumination , pose and expression conditions , the performance of AFR systems need to be improved .

人脸问题主要包括：人脸检测、人脸跟踪、人脸识别，以及其衍生出来的姿态和表情分析四个应用领域。

Human face problems consist of four parts : human face detection , human face tracking , identification of human face and the interrelated pose and expression .

但是在环境不可控的情况下，由于光照、姿态、表情、遮挡等变化的影响，已有的人脸识别算法性能大大下降，其应用范围受到较大的限制。

While the face recognition algorithm performance degrades under uncontrolled environment such as variant illumination , head poses , facial expressions , occlusion on face and so on .

实验结果表明，该算法对视频中的人脸有姿态、表情以及光照变化时均能进行可靠跟踪，是一种行之有效的人脸跟踪方法。

Experimental results show that the face in video with gesture 、 facial expressions and light changes can be reliable tracked , it is an effective method of face tracking .

运行结果表明，此算法对不同图片有比较强的适应性，对姿态与表情鲁棒性好，能够比较准确的检测出人脸的位置。

The result of simulation shows that this algorithm has strong adaptability for different pictures , robustness for posture and facial expression . Meanwhile , it can accurately detect the face position .

三维人脸识别有望解决二维人脸识别中面临的光照、姿态和表情等影响识别效果的瓶颈问题。因此成为众多科研机构研究的重点。

The 3d face recognition is expected to solve 2d face recognition bottlenecks of effecting identifying by lighting , poses and expressions . Therefore it becomes the focus of many institutions research .

同时，由于年龄，姿态，表情，光照等因素对人脸图像的影响，人脸识别面临多方面的挑战。

At the same time , because of the effect of age , posture , facial expression , illumination and other factors on the face image , face recognition is facing many challenges .

因此，如何提高人脸图像的识别率和降低人脸识别的时间消耗，以及提高人脸识别算法对光照、姿态和表情的鲁棒性成为研究者们关注的焦点。

Therefore , how to improve the recognition rate , reduce the time consumption , and improve the robust on illumination , pose and expression of face recognition algorithms become the focus of researchers .

目前的二维人脸识别系统在受控条件下能取得很好的性能，但在光照、姿态、表情等因素影响下性能将急剧下降。

2D face recognition system can achieve good performances under controlled conditions . But its performance will drop drastically under the influence of some factors , such as illumination , pose , and expression variations .

但如何克服背景的嘈杂，人脸姿态及表情的变化，人脸的部分及完全遮挡，摄像机的运动等的影响的难度较大，使之成为一项十分具有挑战性的工作。

But how to overcome the problems caused by the background interference , the changes of facial expressions , the partial or total occlusion and the motions of camera makes it quite a challenging work .

近些年来，面部特征点定位技术已经得到了广泛研究，但是受到光照、姿态、表情以及遮挡等因素的影响，其性能还需要进一步提高。

In recent years , although the facial features location has been extensively studied , existing methods is still influenced by the illumination , pose , expression and occlusion . Its performance needs to be further improved .

例如：姿态、表情、年龄、遮挡、光照等因素依然严重影响人脸检测与识别的效果，表情识别的研究仍处于起步阶段，理论和方法仍有待完善。

For example , pose , facial expression , age , occlusion , illumination and other factors still heavily influence the effect of face detection and recognition . Facial expression recognition research is still in its infancy , so the theory and method remains to be improved .

分析了主成分分析法在特征向量选择方面的问题，提出了一种基于主成分分析和人工神经网络结合的多姿态、表情准正面人脸图像识别方法。

This thesis including : ( 1 ) After analyzing the application of principal component analysis and prevailing face recognition technology , a multi-pose approximate frontal face recognition method based on principal component analysis ( PCA ) and back propagation ( BP ) neural network is proposed .

针对多姿态、多表情人脸识别的情况介绍了一种改进的人脸识别方法&基于对称性特征半脸（based-symmetricalhalf-PCA，SHPCA）的人脸识别方法。

A improved approach-based-symmetrical half-PCA ( SHPCA ) is introduced for recognizing pose and expression varied human faces .

实验证明，这种方法在复杂姿态和复杂表情以及戴眼镜的情况下有很强的稳健性。

Experimental results are given to show the robustness and effectiveness of the method in complex conditions .

译：有时可以把身体语言，或者叫非语言文字的交流，分成五大类：（1）身体的姿态和面部表情；

Body language , or NVC signals , are sometimes categorised into five kinds : 1.body and facial gestures ;

有时可以把身体语言，或者叫非语言文字的交际信号，分成五大类：（1）身体的姿态和面部表情；

Body language , or NVC signals , are sometimes categorised into five kinds : 1 . body and facial gestures ;

人脸图像处理包括人脸检测、人脸识别、人脸跟踪、姿态估计和表情识别等。

Research efforts in face image processing include face detection , face recognition , face tracking , pose estimation , expression recognition and so on .

本文致力于从目光语，手势语，身体姿态，面部表情，体触语方面对不同文化的身势语进行对比。

This article devotes to a comparison and contrast of body language in different cultures in terms of eye language , gestures , postures , facial expressions and touch .

情感识别是情感计算的一个重要部分，它研究的内容包括语音信号、身体姿态、面部表情和生理信号等方面。

As an important part of affective computing , emotion recognition mainly contains diverse studies including voice signals , body posture , facial expressions and physiological signals and so on .

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。

It finds applications in various areas , such as face detection , face recognition , gesture recognition , expression recognition , face image compression and reconstruction , and face cartoon .

人际交流中，仅有7%至35%的内容由口头词汇构成，其余的则由肢体语言来传达：手势、身体姿态、面部表情、肢体近距离接触等。

Words comprise but a mere 7 to 35 percent of human communication . The rest comes via body language : gestures , posture , facial expressions , proximity and touch .