ASM与彩色Gabor特征相结合的人脸关键特征点提取  

ASM and Color Gabor Features for Facial Feature Extraction

作　　者：朱杰[1] 唐振民[1] 

机构地区：[1]南京理工大学计算机学院,南京210094

出　　处：《计算机科学》2010年第4期265-268,共4页Computer Science

基　　金：国家部委项目基金(编号:51316080101)资助

摘　　要：提出一种ASM(active shape Model)与彩色Gabor特征相结合的提取人脸关键特征点的方法。该方法首先通过瞳孔的精确定位来辅助完成人脸形状模型的初始化;然后采取全局特征与局部特征相结合的方法来共同实现对特征点的定位;最后选取人脸图像中的关键特征点的特征信息,结合彩色Gabor特征进行提取,进而快速准确地得到人脸关键特征点。实验表明,与传统的ASM算法比较,加入了彩色信息的改进算法对特征点定位有显著的提高。To improve active shape ModeI（ASM） accuracy in facial feature points location in facial images,an improved ASM based algorithm was proposed. First, the irises were localized and utilized to initialize the shape model. Second, global face features with salient features were employed to constrain the movement of feature points;at last, in order to improve ASM, Color Gabor features was used to extract edges and corner points for feature, so we could get the key facial feature points quickly and accurately. Experimental results show that our algorithm performs significantly better than the traditional ASM.

关 键 词：特征点定位 ASM方法 彩色Gabor 特征提取 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]