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改进的多模板ASM人脸面部特征定位算法

An Improved Algorithm for Facial Feature Location by Multi-template ASM

  • 摘要: 为了提高主动形状模型(ASM)算法在人脸平滑区域检测的准确性,提出一种先利用全局模板进行总体定位,再利用局部模板进行局部定位的改进的多模板ASM算法.在局部定位过程中,首先在各模板特征点中构建窄条带,然后利用Closed-form算法对窄条带区域进行纹理分割,最后利用局部模板与图像进行匹配,得到人脸特征点位置信息.实验结果表明,与传统ASM算法相比,该算法显著改善了纹理平滑区域特征点定位不精确的问题,并提高了对各特征点的提取精度.

     

    Abstract: To improve the active shape model(ASM) location accuracy in smooth regions in facial images,this paper proposes an improved multi-template ASM based algorithm which performs a coarse location by a global template at first,then followed by a local template for refinement.At the second stage,a narrow strip-map is first constructed on the feature points of each template,and then a Closed-form algorithm is employed to perform texture segmentation on the narrow strip-map;finally local templates are matched to the image to obtain feature-point information.Experimental results show that our algorithm significantly improves the location accuracy of the traditional ASM in smooth regions,and enhances the detection accuracy of all the feature points.

     

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