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结合局部关键点集与测地线的三维人脸识别

3D Face Recognition Combining Local Keypoints with Isogeodesic Curves Zhang Hongying

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摘要

为了克服面部表情变化导致的三维人脸识别精度不高的问题,提出了一种结合局部关键点集与测地线的三维人脸识别算法。首先,根据表情变化对人脸识别具有分区域影响的特性,将三维人脸划分出刚性区域和非刚性区域;然后将由鼻部和眼部组成的区域作为刚性区域,进行有效关键点检测,提取多种几何特征,构成局部描述子,进行相似度匹配;接着在非刚性区域提取测地线环带并进行相似度匹配;最后将两个区域的匹配程度进行加权融合,得到最终的匹配结果。该算法分别在Bosphorus和FRGC v2.0数据库上进行了实验验证,结果表明算法识别率分别达到了97.01%和98.63%,由此证明本文算法对三维人脸的表情变化有较强的稳健性。

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中图分类号:TP391.4

DOI:10.3788/LOP57.221503

所属栏目:机器视觉

基金项目:国家重点研发计划、国家自然科学基金民航联合研究基金重点项目、中央高校基本科研业务费项目中国民航大学专项;

收稿日期:2020-03-09

修改稿日期:2020-04-23

网络出版日期:2020-11-01

作者单位    点击查看

张红颖:中国民航大学电子信息与自动化学院, 天津 300300
杨维民:中国民航大学电子信息与自动化学院, 天津 300300
王汇三:中国民航大学电子信息与自动化学院, 天津 300300

联系人作者:张红颖(carole_zhang0716@163.com)

备注:国家重点研发计划、国家自然科学基金民航联合研究基金重点项目、中央高校基本科研业务费项目中国民航大学专项;

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引用该论文

Zhang Hongying,Yang Weimin,Wang Huisan. 3D Face Recognition Combining Local Keypoints with Isogeodesic Curves Zhang Hongying[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221503

张红颖,杨维民,王汇三. 结合局部关键点集与测地线的三维人脸识别[J]. 激光与光电子学进展, 2020, 57(22): 221503

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