3D Facial Gender Classification Based on Multi-angle LBP Feature
3D Facial Gender Classification Based on Multi-angle LBP Feature
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DOI：
10.3724/sp.j.1004.2012.01544
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
H. Zhao;Yi-Fan Yang;Zheng-guang Xu
中科院分区：
文献类型：
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作者：
H. Zhao;Yi-Fan Yang;Zheng-guang Xu
人脸性别分类是一个极具挑战性的课题，S提出了一系列基于三维人脸的性别分类方法。首先通过局部区域迭代最近点配准进行自动前置调整；然后在不同视角下对深度缩略图进行俯仰旋转并提取多角度的线性BP特征；最后使用支持向量机分类器进行训练和预测。该算法在CASIA数据库上进行了实验，对于数据库中的中性人脸，最高正确分类率为98.374%。
Facial gender classification is a challenging topic,and it s still not perfect until now.In this paper,we propose a series of methods of gender classification based on three-dimension faces.Automatic front-pose adjustment is needed through local region iterative closest point(ICP) registration firstly;then we do pitching rotating and extract multi-angle LBP features from depth thumbnail map in di?erent viewing angles;at last,we use support vector machine(SVM) classifier to do training and prediction.This algorithm has been experimented on CASIA database,and for the neutral faces in this database,we can get a highest correct classification rate of 98.374%.