系统应用本论文中提到的算法进行真实感人脸合成，实验结果验证了算法的可行性。
System use the method mentioned in paper, the result of the test has verified its feasibility.
人脸是我们最熟悉的器官，但真实感人脸合成却是计算机图形学领域中最困难的问题之一。
The human face is the most familiar organ to us, but it is a difficult problem in the area of computer graphics to synthesize realistic human face.
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.
我们的方法能够较好地满足商图像方法的理论前提，从而达到更好的图像合成效果和人脸识别性能。
Our method can meet the theoretical prerequisites of quotient image method, and achieve better image synthesis and face recognition results.
长期以来，在计算机图形学、图像处理和计算机视觉这三个学科领域中，人脸的计算机模拟合成一直是个研究的热点。
Since a long time, facial image synthesis has been a hot research topic in the fields of computer graphics, image process and computer vision.
针对这些问题，本文提出基于形变褶皱合成的逼真人脸动画。
To solve them, this paper propose realistic facial animation based on contour change-wrinkle synthesis.
除了图像分析合成，模型基编码中还有很重要的一个部分就是特定人脸模型的生成。
Besides image analysis and synthesis, model-based coding research still has an important direction to reconstruct an individual facial model.
使用该模型，加上一些必要的后期处理工作，就可以通过输入的语音信号合成语种无关的、平滑的、并富有真实感的人脸语音动画。
Using this model, together with some necessary post-process work, it can synthesize smooth, realistic face speech animation independent of classification of language only with speech signal.
人脸图像合成是新一代人机交互中的重要技术。
Facial expression synthesis is an important technique in human computer interactions.
本文研究了MPEG - 4中人脸视频对象的模型基编码，对整个系统进行了全面的分析，将系统按编解码结构分成分析和合成两部分。
In this thesis, MPEG-4 model-based coding for facial video object is investigated. The whole codec system is generally discussed and divided into two parts of Analysis and Synthesis.
最后通过对图像划分区域，分段完成纹理贴图，合成3d人脸模型。
Finally texture mapping is completed according to different regions on the face and thus the 3d face model is synthesized.
AAM人脸特征点定位模块是关键模块，其定位结果直接影响人脸表情动画合成效果。
AAM facial feature points positioning module is the master key for its orientation result directly influence the synthetic effect of the facial expression animation.
该算法将人脸特征提取与图像复合相结合，无需3维人脸模型重建，自动合成具有源图像主要五官特征的结果图像。
This paper combines facial features extraction with image fusion algorithm, so that we can automatically obtain synthesis results without using 3d facial models.
实验结果表明：该方法能有效地合成无眼镜的正面人脸图像。 原始戴眼镜人脸图像的识别率是50.1%，合成的无眼镜正面人脸图像的识别率是99.4%。
Test results show that the method can effectively synthesize eyeglassless facial images, with the subseguent recognition rate increased from 50.1% to 99.4%.
利用HMM的统计特性，对HMM模型结构进行改动，使其成为人脸语音动画合成中语音特征到图像特征的映射模型。
This paper takes advantage of HMM's statistic characters. With a little modification on HMM structure, it gets a mapping model from speech to image.
进而提出，五官位置和拓扑结构可组合成具体图形意义上的结构关系，这种结构关系将整体人脸分解成有序的特徵集。
The positions of facial features and the topology constituted the structure in a concrete object image, and this structure disintegrated the holistic face into a regular set of features.
当给出一张测试人脸图像时，我们利用因素分解模型的“转移”算法合成测试人脸在训练集已有表情下的图像和训练集人脸在测试人脸表情下的图像。
By given a test image, the expressions in the training set can be "translate" to the input image by using factorization model and vice versa.
当给出一张测试人脸图像时，我们利用因素分解模型的“转移”算法合成测试人脸在训练集已有表情下的图像和训练集人脸在测试人脸表情下的图像。
By given a test image, the expressions in the training set can be "translate" to the input image by using factorization model and vice versa.
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