计算机科学 ›› 2010, Vol. 37 ›› Issue (4): 265-.
• 图形图像及体系结构 • 上一篇 下一篇
朱杰,唐振民
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ZHU Jie,TANG Zhen-min
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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Labor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。
关键词: 特征点定位,ASM方法,彩色Gabor,特征提取
Abstract: To improve active shape Modcl(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
Key words: Feature points location, ASM, Color Gabor features, Feature extraction
朱杰,唐振民. ASM与彩色Labor特征相结合的人脸关键特征点提取[J]. 计算机科学, 2010, 37(4): 265-. https://doi.org/
ZHU Jie,TANG Zhen-min. ASM and Color Gabor Features for Facial Feature Extraction[J]. Computer Science, 2010, 37(4): 265-. https://doi.org/
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