计算机应用与软件2016，Vol.33Issue(9)：139-142,4.DOI:10.3969/j.issn.1000-386x.2016.09.033
基于深度自编码器网络的人脸特征点定位方法
FACIAL LANDMARK LOCALISATION APPROACH BASED ON DEEP AUTOENCODER NETWORKS
摘要
Abstract
Facial landmarks localisation methods using deep learning network technology have achieved prominent effect.However,the localisation of larger number of facial landmarks (more than 50 points)still have lots of challenges due to the complex diversities in face images caused by pose,expression,illumination and occlusion,etc.This paper designs a three-level cascaded autoencoder network,which are employed to locate a large number of facial landmarks in a coarse-to-fine manner.The first level of the network estimates facial contour and component positions directly by tacking the whole face image as input,which divides landmarks into three parts (eyes and nose,mouth, and facial contour)for the next localisation steps;the following two level of the network estimate and refine the landmarks of each part respectively.Experiments conducted on LFPW,HELEN databases show that the approach can improve the accuracy and robustness of facial landmark localisation.关键词
人脸特征点定位/深度学习/自编码器网络/逐步求精Key words
Facial landmark localisation/Deep learning/Autoencoder networks/Coarse-to-fine分类
信息技术与安全科学引用本文复制引用
梁洋洋,陈宇,杨健..基于深度自编码器网络的人脸特征点定位方法[J].计算机应用与软件,2016,33(9):139-142,4.基金项目
国家自然科学基金面上项目（61472187）。 （）
