提出了一种改进的主动形状模型，并将其用于人脸面部特征定位的研究。
An improvement ASM is proposed and this model is applied to facial feature localization.
论文的创新性成果包括：1。提出了一种改进的主动形状模型，并将其用于人脸面部特征定位的研究。
The innovative achievements of the thesis include:1. An improvement ASM is proposed and this model is applied to facial feature localization.
主动外观模型是进行人脸面部特征定位和人脸识别的有效方法，近年来已成为图像处理等领域的研究热点。
Active Appearance Models (AAMs) is an effective method of facial recognition and facial feature location, and has become a research hotspot in image processing areas.
本文还研究了基于AAM的面部特征定位方法，分析了灰度模型参数及表观模型参数在人脸重构中的作用。
Active appearance model (AAM) is also studied for the localization of facial features. The parameters of texture model and appearance model are studied in detail in reconstruction of face images.
本文首先在对人脸检测、人脸面部特征定位技术的相关文献进行综述的基础上，提出了人脸检测技术融合算法。
In this thesis, I present a novel face detection framework based on a face detection algorithm merged with some advanced algorithms.
人脸面部的关键特征点定位既是人脸识别研究领域中的一个关键问题，也是计算机视觉和图形学领域的一个基本问题。
Facial feature point location is one of the fundamental and crucial problems in the field of facial recognition, computer vision and graphics.
本文采用该算法训练人脸面部特征检测器，提取区域的几何中心进行面部特征点定位，获取以双眼和嘴巴为特征顶点的人脸特征三角形。
The thesis uses the method to train face feature classifier, to get the face feature points and build face feature triangle that uses eyes and mouth as vertexes.
本文工作包括：侧面人脸的检测与定位，侧面人脸面部特征的定位与提取和侧面人脸的识别等内容。
The main work in this paper include: side face image detection, side face feature extraction and side face recognition and so on.
提出基于积分投影法辅以人的面部所遵循的比例关系原理的脸部特征定位算法。
An algorithm of locating face image is presented based on integration projection theory and transcendent knowledge of human face.
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。
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。
It aims to locate the facial feature points and the shape information of eyes, mouth and so on based on the facial detect.
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