Image based facial feature points extraction.
基于照片的人脸特征点提取。
Precise facial feature points extraction is the key to solve these problems.
特征点精确定位是解决这些问题的关键。
On the research of human cranium and head muscle, the definition of the facial feature points is given.
在研究了人脸的颅骨、肌肉组织特点的基础上，给出了人脸特征点的定义及选取规则。
The paper integrates with physiological basis of facial structure, and defines facial feature points set;
本文结合人脸结构生理学基础，定义人脸的特征点集；
According to the characteristics of facial motion, the facial feature points are divided into two subsets.
针对人脸运动特点，将面部特征点分为具有复杂运动模式和简单运动模式的特征点集。
It aims to locate the facial feature points and the shape information of eyes, mouth and so on based on the facial detect.
在人脸检测的基础上，面部关键的特征点定位试图定位人脸面部主要特征点的位置以及眼睛和嘴巴等主要器官的形状信息。
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。
System mainly divided into three modules:AAM facial feature points positioning module, FAP conversion module, and MPEG-4 model animation module.
系统主要可分为三大模块：AAM人脸特征点定位模块、FAP转换模块、MPEG-4模型动画实现模块。
AAM facial feature points positioning module is the master key for its orientation result directly influence the synthetic effect of the facial expression animation.
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。
A novel strategy, which is different from the traditional texture mapping methods, is proposed for generating such a kind of dynamic facial textures according to the motion of facial feature points.
与传统的纹理映射方法不同，提出一种根据脸部特征点运动来生成脸部动态纹理的新方法。
Applying a D-triangulation on the facial feature points, a precise and topological isomorphic mapping is established between 3d mesh and texture. The texture mapping with high quality can be obtained.
该方法对人脸特征点集做三角剖分，在纹理图像和三维网格之间建立了一个准确的拓扑同构映射关系，从而得到高真实度的纹理映射。
Based on the different facial characters of ID photo, the paper proposes several methods to locate feature points for extracting the facial feature exactly.
根据证件照片中脸部各个对象的不同特征，分别采用不同的定位方法进行定位。
It discusses the method of detecting these points, the expression-independent vectorization of human face and also the arrangement and optimization of the facial feature database.
文章给出了这些特征点的提取方法，对与表情变化无关的人脸的矢量化方法进行了研究，并对人脸特征数据库设计和优化进行了探讨。
However, when estimating facial shapes using current facial landmarks detecting methods, the locating error of feature points around the mouth region is relatively large.
然而，用现有的人脸特征点定位算法进行人脸形状估计时，嘴巴区域特征点的定位误差相对较大。
However, when estimating facial shapes using current facial landmarks detecting methods, the locating error of feature points around the mouth region is relatively large.
然而，用现有的人脸特征点定位算法进行人脸形状估计时，嘴巴区域特征点的定位误差相对较大。
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