3D Facial Gender Classification Based on Multi-angle LBP Feature

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%.